{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Volatility tracking\n",
    "\n",
    "This is another notebook where I use the Kalman filter to track hidden variables.      \n",
    "This time it's the turn of **volatility**!     \n",
    "Well, actually I will track the variance, but the concept is the same.\n",
    "\n",
    "I will use the values simulated by a Heston process, and implement several methods to track the (hidden) volatility process.\n",
    "We will compare the simple \"rolling\" method with the very famous GARCH(1,1) method, and we will see that the Kalman filter is slightly superior to both of them.\n",
    "\n",
    "This notebook also contains a small digression on the Variance Gamma process, which however is not related to the main theme and therefore you can skip it if you are not interested.\n",
    "\n",
    "In this notebook, I will make use of the [ARCH](https://arch.readthedocs.io/en/latest/index.html) library, which is not present in the docker container that I suggested to use. So it is better to create a virtual environment with the packages suggested in the \"requirements.txt\" file, or simply install ARCH by yourself on your system.\n",
    "\n",
    "## Contents\n",
    "   - [Heston Path generation](#sec1) \n",
    "      - [Log-return analysis](#sec1.1)\n",
    "      - [Hypothesis testing](#sec1.2)\n",
    "      - [A digression on the Variance Gamma process](#sec1.3)\n",
    "   - [Garch(1,1)](#sec2)\n",
    "      - [GARCH with the arch library](#sec2.1)\n",
    "      - [GARCH from scratch](#sec2.2)\n",
    "      - [Rolling variance](#sec2.3)\n",
    "   - [Kalman filter](#sec3)\n",
    "      - [Linear Gaussian State Space Model](#sec3.1)\n",
    "      - [Algorithm implementation](#sec3.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import scipy.stats as ss\n",
    "import statsmodels.api as sm\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from functions.Processes import Heston_process, VG_process, GARCH\n",
    "from arch.unitroot import PhillipsPerron, KPSS, ADF\n",
    "from arch import arch_model\n",
    "from statsmodels.graphics.gofplots import qqplot\n",
    "from statsmodels.tsa.stattools import pacf\n",
    "import matplotlib.gridspec as gridspec\n",
    "from functions.probabilities import VG_pdf\n",
    "from scipy.integrate import quad\n",
    "from scipy.optimize import minimize\n",
    "#from importlib import reload"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec1'></a>\n",
    "# Heston path generation\n",
    "\n",
    "Let us consider a stock price $\\{S_t\\}_{t\\geq 0}$ following a Heston process. We introduced the Heston process in the notebook **1.4**, but it is better to recall the SDE: \n",
    "\n",
    "$$ \\begin{cases}\n",
    "dS_t = \\mu S_t dt + \\sqrt{v_t} S_t dW^1_t \\\\\n",
    "dv_t = \\kappa (\\theta - v_t) dt + \\sigma \\sqrt{v_t} dW^2_t \n",
    "\\end{cases}$$\n",
    "\n",
    "The process $\\{v_t\\}_{t\\geq 0}$ is the variance process and follows a CIR process (see notebook **1.2**).     \n",
    "\n",
    "The parameters are:\n",
    "- $\\mu$ drift of the stock process\n",
    "- $\\kappa$ mean reversion coefficient of the variance process\n",
    "- $\\theta$ long term mean of the variance process \n",
    "- $\\sigma$  volatility coefficient of the variance process\n",
    "- $\\rho$ correlation between $W^1$ and $W^2$.\n",
    "\n",
    "I will simulate the process considering `N=2500` time points and `T=10` years. This is quite realistic as in ten years there are about 2500 days."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 2500                                                      # time points \n",
    "T = 10                                                        # time in years  \n",
    "T_vec, dt = np.linspace(0,T,N, retstep=True )                 # time vector and time step\n",
    "S0 = 100                                                      # initial price\n",
    "v0 = 0.04                                                     # initial variance \n",
    "mu = 0.1; rho = -0.1; kappa = 5; theta = 0.04; sigma = 0.6    # alternative values: rho=-0.3 kappa=15 sigma=1\n",
    "std_asy = np.sqrt( theta * sigma**2 /(2*kappa) )              # asymptotic standard deviation for the CIR process\n",
    "assert(2*kappa * theta > sigma**2)                            # Feller condition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us generate the path using the function `Heston_process.path`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(seed=42) \n",
    "Hest = Heston_process(mu=mu, rho=rho, sigma=sigma, theta=theta, kappa=kappa)\n",
    "S, V = Hest.path(S0, v0, N, T)      # S is the stock, V is the variance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,4))\n",
    "ax1 = fig.add_subplot(121); ax2 = fig.add_subplot(122)\n",
    "ax1.plot(T_vec, S )\n",
    "ax1.set_title(\"Heston model, Stock process.\"); ax1.set_xlabel(\"Time\"); ax1.set_ylabel(\"Stock\")\n",
    "ax2.plot(T_vec, V )\n",
    "ax2.set_title(\"Heston model, Variance process.\"); ax2.set_xlabel(\"Time\"); ax2.set_ylabel(\"Variance\")\n",
    "ax2.plot(T_vec, (theta + std_asy)*np.ones_like(T_vec), label=\"1 asymptotic std dev\", color=\"black\" )\n",
    "ax2.plot(T_vec, (theta - std_asy)*np.ones_like(T_vec), color=\"black\" )\n",
    "ax2.plot(T_vec, theta*np.ones_like(T_vec), label=\"Long term mean\" )\n",
    "ax2.legend(loc=\"upper right\"); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec1.1'></a>\n",
    "## Log-return analysis\n",
    "\n",
    "Let us compute the **log-returns** and **linear (or net) returns**.       \n",
    "It turns out that it is almost the same to work with log-returns or linear returns.     \n",
    "For small $\\Delta t$, we can use a first order Taylor expansion (around 1):\n",
    "\n",
    "$$ \\log \\frac{S_{t+\\Delta t}}{S_t} \\; \\approx \\; \\frac{S_{t+\\Delta t}}{S_t} -1 $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "ret_log = np.log(S[1:]/S[:-1])        # log returns\n",
    "ret_pct = S[1:] / S[:-1] - 1          # linear net returns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Fit of Variance Gamma and Student t\n",
    "\n",
    "I will explain in the [VG Section](#sec1.3) why I chose the Variance Gamma distribution among many others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "VG parameters: 0.0005194485663832025 -0.05548824186766799 0.20503868767677264 0.003450210420172355\n"
     ]
    }
   ],
   "source": [
    "VG = VG_process()\n",
    "VG.fit_from_data( ret_log, dt, \"Nelder-Mead\" )  # or \"MM\" (methods of moments), or \"L-BFGS-B\" that does not work\n",
    "print(\"VG parameters:\", VG.c, VG.theta, VG.sigma, VG.kappa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Student-t parameters (3.5313949443738206, 0.0003999362308227026, 0.009120671213235513)\n"
     ]
    }
   ],
   "source": [
    "params = ss.t.fit(ret_log)\n",
    "print(\"Student-t parameters\", params)   # degrees of freedom, location, scale"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us compute the mean and standard deviation for both log-returns and linear returns. I present the normalized values i.e. the values computed for $T=1$.     \n",
    "Adding the approximated Itô correction $\\frac{1}{2}\\theta$, the two means becomes almost equal (see below for a better explanation). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Log-returns, normalized mean=0.0673 and std=0.2065\n",
      "Corrected mean=0.0873 by approximated Itô correction\n",
      "Linear returns, normalized mean=0.0887 and std=0.2066\n"
     ]
    }
   ],
   "source": [
    "mean_log = ret_log.mean(); std_log = ret_log.std()\n",
    "mean_pct = ret_pct.mean(); std_pct = ret_pct.std()\n",
    "print(\"Log-returns, normalized mean={:.4f} and std={:.4f}\".format(mean_log/dt, std_log/np.sqrt(dt)) )\n",
    "print(\"Corrected mean={:.4f} by approximated Itô correction\".format(mean_log/dt + 0.5*theta) )\n",
    "print(\"Linear returns, normalized mean={:.4f} and std={:.4f}\".format(mean_pct/dt, std_pct/np.sqrt(dt)) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below, you can see the returns histogram with some fitted distributions, the qq-plot and the plot of the log-return process.    \n",
    "As expected, the normal distribution underestimates the mass around the mean. From the histogram it is difficult to notice the presence of heavy tails. For this reason I included the qqplot as well.    \n",
    "The plot of the log-returns dynamics includes the mean and standard deviation levels. It clearly exhibits volatility clustering.\n",
    "\n",
    "<a id='hist'></a>\n",
    "##### Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(ret_log.min(), ret_log.max(), 200)\n",
    "fig = plt.figure(figsize=(16,9));  gs = gridspec.GridSpec(2, 2, height_ratios=[2,1])\n",
    "gs00 = gs[1,:].subgridspec(1, 2, width_ratios=[2,3])\n",
    "ax1 = fig.add_subplot(gs[0, :]); ax2 = fig.add_subplot(gs00[0, 0]); ax3 = fig.add_subplot(gs00[0, 1])\n",
    "ax1.plot(x, ss.norm.pdf(x, mean_log, std_log), color='olivedrab', label=\"Normal density\")\n",
    "ax1.plot(x, ss.t.pdf(x, loc=params[1], scale=params[2], df=params[0]), color=\"darkorange\",\n",
    "         label=\"Stud-t, df={}\".format(params[0].round(2) ))\n",
    "ax1.plot(x, VG_pdf(x, dt, VG.c, VG.theta, VG.sigma, VG.kappa ), color='indigo', label=\"VG density\")\n",
    "ax1.plot(x, VG_pdf(x, dt, VG.c+VG.theta*dt, 0, np.sqrt(VG.var), VG.kappa ), \n",
    "         color='darksalmon', label=\"VG approximated density\")\n",
    "ax1.hist(ret_log, density=True, bins=200, facecolor=\"LightBlue\", label=\"Log-returns\")\n",
    "ax1.legend(); ax1.set_title(\"Log-returns histogram\")\n",
    "ax2.set_title(\"Log-returns qqplot\");  qqplot(ret_log, line='s', ax=ax2)\n",
    "ax3.plot(T_vec[1:], ret_log); ax3.set_title(\"Log-return dynamics\")\n",
    "ax3.plot(T_vec[1:], (mean_log + std_log)*np.ones(N-1), label=\"1 std dev\", color=\"black\" )\n",
    "ax3.plot(T_vec[1:], (mean_log - std_log)*np.ones(N-1), color=\"black\" )\n",
    "ax3.plot(T_vec[1:], mean_log*np.ones(N-1), color=\"orange\", label=\"mean\" ); ax3.set_xlabel(\"Time\")\n",
    "ax3.legend(); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From now on, the quantity of interest will be the **stock return** $R_t$.    \n",
    "As we have seen above, there is no big difference between using log-returns or linear returns. \n",
    "\n",
    "Since we will work with a time series of data, it is better to consider a discrete-time model (with $\\Delta t = 1$), that can be derived from the discretization of the SDE we have seen before.\n",
    "\n",
    "1) Linear returns, $ R_{t+1} := \\frac{S_{t+1}}{S_t} -1  $:\n",
    "\n",
    "We can discretize the equation of the process $\\{S_t\\}_{t\\geq0}$ in the Heston SDE introduced on top of this notebook (the Euler-Maruyama discretization procedure is presented in the notebook **1.2**):\n",
    "\n",
    "$$ R_{t+1} = \\mu + \\sqrt{v_t} \\Delta W_{t} $$\n",
    "\n",
    "with $\\Delta W_{t} = W_{t+1} - W_{t}$.\n",
    "\n",
    "2) Log-returns,  $ R_{t+1} := \\log \\frac{S_{t+1}}{S_t} $:\n",
    "\n",
    "You should make a change of variable into the Heston SDE (see what I did in the notebook **1.4**) and then discretize. \n",
    "\n",
    "$$ R_{t+1} = \\mu - \\frac{1}{2}v_t + \\sqrt{v_t} \\Delta W_{t} $$\n",
    "\n",
    "In the linear returns equation we have a constant drift $\\mu$, but in the log-return equation the drift $\\mu - \\frac{1}{2}v_t$ is stochastic.\n",
    "\n",
    "Since we are interested in the volatility, there is no need of a drift term. It turns out that it is almost always possible to detrend a time series.   \n",
    "If the trend is constant we can simply define $\\tilde R_{t} := R_{t} - \\mu$. If the trend is stochastic, detrending is more complicated but still possible.    \n",
    "In particular, in the process above the effect of the stochasticity in the trend is negligible for big values of $T$. Since the trend is a mean reverting process, we can approximate the mean with its long term mean $\\mathbb{E}\\big[ v_t \\big] \\approx \\theta$. Let us check it is correct.    \n",
    "From the [CIR conditional expectation](https://en.wikipedia.org/wiki/Cox%E2%80%93Ingersoll%E2%80%93Ross_model#Properties) formula, we can use the tower property:\n",
    "\n",
    "$$ \\mathbb{E}\\big[ v_t \\,\\big|\\, \\mathcal{F}_0 \\big] = \\mathbb{E}\\bigg[ \\mathbb{E}\\big[ v_t \\big| v_{t-1} \\big] \\, \\bigg|\\, \\mathcal{F}_0 \\bigg] = \\mathbb{E}\\bigg[ v_{t-1} e^{-\\kappa \\Delta t} + \\theta (1-e^{-\\kappa \\Delta t}) \\, \\bigg|\\, \\mathcal{F}_0 \\bigg] = \\mathbb{E}\\big[ v_{t-1} \\, \\big|\\, \\mathcal{F}_0 \\big] e^{-\\kappa \\Delta t} + \\theta (1-e^{-\\kappa \\Delta t})  $$\n",
    "\n",
    "For $t \\gg 0$ ($t$ much bigger than zero) we can write $\\mathbb{E}\\big[ v_t \\,\\big|\\, \\mathcal{F}_0 \\big] \\approx \\mathbb{E}\\big[ v_{t-1} \\,\\big|\\, \\mathcal{F}_0 \\big] \\approx \\mathbb{E}\\big[ v_t \\big]$ where the dependency on the initial information $\\mathcal{F}_0$ decays.\n",
    "Solving the equation we get $\\mathbb{E}\\big[ v_t \\big] \\approx \\theta$. \n",
    "\n",
    "We can detrend the series by redefining $\\tilde R_{t} := R_{t} - \\mathbb{E}[R_{t}] = R_{t} - \\mu + \\frac{1}{2}\\theta$.     \n",
    "I called the term $\\frac{1}{2}\\theta$, *approximated Itô correction*.  \n",
    "\n",
    "We obtain a unified model that works for both linear and log returns (we can suppress the tilde):\n",
    "\n",
    "$$ R_{t+1} = \\sqrt{v_t}\\, \\epsilon_{t+1} $$\n",
    "\n",
    "with $\\epsilon_t \\sim \\mathcal{N}(0,1)$ for each $t$. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec1.2'></a>\n",
    "## Hypothesis testing\n",
    "\n",
    "Let us investigate the statistical properties of this log-return time series.\n",
    "\n",
    "For this purpose I want to perform some tests:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Stationarity tests:\n",
    "\n",
    "- The Augmented Dickey-Fuller test [wiki](https://en.wikipedia.org/wiki/Augmented_Dickey%E2%80%93Fuller_test)    \n",
    "The null hypothesys is that the process is unit root.\n",
    "\n",
    "\n",
    "- The Phillips-Perron test [wiki](https://en.wikipedia.org/wiki/Phillips%E2%80%93Perron_test)     \n",
    "The test is robust with respect to unspecified autocorrelation and heteroscedasticity. The null hypothesys is that the process is unit root.\n",
    "\n",
    "\n",
    "- Kwiatkowski–Phillips–Schmidt–Shin tests [wiki](https://en.wikipedia.org/wiki/KPSS_test)    \n",
    "The null hypothesys is that the process is NOT unit root.\n",
    "\n",
    "Let us also conside the [Jarque-Bera](https://en.wikipedia.org/wiki/Jarque%E2%80%93Bera_test) test for normality and the [Ljung-Box](https://en.wikipedia.org/wiki/Ljung%E2%80%93Box_test) test for autocorrelation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Augmented Dickey Fuller test: p-value =  0.0\n",
      "Phillips Perron test: p-value =  0.0\n",
      "KPPS test: p-value =  0.817\n",
      "\n",
      "Jarque-Bera (H0=normal), p-value =  0.0\n",
      "Ljung-Box test (H0=independent) for lag 1 to 3, p-values =  [0.34843522 0.4224824  0.61618723]\n",
      "Ljung-Box test on the squared returns, p-values =  [1.14275887e-18 3.49742191e-38 1.86949489e-47]\n"
     ]
    }
   ],
   "source": [
    "print(\"Augmented Dickey Fuller test: p-value = \", ADF(ret_log, trend='nc').pvalue)\n",
    "print(\"Phillips Perron test: p-value = \", PhillipsPerron(ret_log, trend='nc').pvalue)\n",
    "print(\"KPPS test: p-value = \", KPSS(ret_log).pvalue.round(4))\n",
    "print()\n",
    "print(\"Jarque-Bera (H0=normal), p-value = \", ss.jarque_bera(ret_log)[1] )\n",
    "print(\"Ljung-Box test (H0=independent) for lag 1 to 3, p-values = \", \n",
    "                           sm.stats.acorr_ljungbox(ret_log, lags=3, return_df=False)[1])\n",
    "print(\"Ljung-Box test on the squared returns, p-values = \", \n",
    "                           sm.stats.acorr_ljungbox(ret_log**2, lags=3, return_df=False)[1] )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Comments:\n",
    "\n",
    "1) The plot of the log-return dynamics suggests that the series is weak stationary (i.e. with constant unconditional mean and variance), but has non-constant conditional variance. This time series clearly exhibits **volatility clustering**.    \n",
    "The first three tests all confirm the weak stationarity!    \n",
    "Since the process has conditional heteroscedasticity, the most appropriate test to use in this case is the PhillipsPerron, which is very robust with respect to nonconstant variances. \n",
    "In [1], it is shown that smooth and periodic variations in the variance have a negligible effect on the ADF test output, which makes it quite reliable as well. \n",
    "\n",
    "2) The Jarque-Bera test confirms what we saw in the histogram and in the qqplot i.e. that the log-returns distribution is not normal.\n",
    "\n",
    "3) The Ljung-Box test on the log-returns shows high p-values. Thus we cannot reject the independence hypothesis (we know that log-returns are independent).  \n",
    "However, the same test applied to the squared log-returns shows very small p-values, confirming the presence of autocorrelation. **Volatility clustering can be detected by checking\n",
    "for correlations between the squared returns.**\n",
    "\n",
    "##### Parameters choice\n",
    "\n",
    "When I chose the parameters of the CIR process $v_t$, I had to select the parameters $\\rho$, $\\kappa$ and $\\sigma$ such that the stationarity and the volatility clusters can be detected from the simulated data.     \n",
    "The mean reversion parameter $\\kappa$ should be big enough to make the process stationary. On the other hand, if $\\kappa$ is too big, the variance process reverts too fast towards its long term mean, and the log-returns do not exhibit the volatility clusters.     \n",
    "If $\\sigma$ is too small, the process always stays near the long term mean, and clusters do not form."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Augmented Dickey Fuller test for the variance process: p-value =  0.0011940495803608193\n",
      "Using the PACF we can calculate phi=0.9833. It is very close to the theoretical value phi=0.9802\n"
     ]
    }
   ],
   "source": [
    "print(\"Augmented Dickey Fuller test for the variance process: p-value = \", ADF(V, trend='nc').pvalue)\n",
    "print(\"Using the PACF we can calculate phi={:.4f}. It is very close to the theoretical value phi={:.4f}\".format(\n",
    "                            pacf(V, nlags=1)[1], np.exp(-kappa*dt)) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The ADF test shows that the process is indeed stationary.\n",
    "\n",
    "We don't know the solution of the CIR equation, but we know its conditional expectation \n",
    "\n",
    "$$\\mathbb{E}\\big[ v_t \\big| v_{t-1}\\big] = \\phi v_{t-1} + const, $$ \n",
    "\n",
    "with $\\phi=e^{-\\kappa \\Delta t}$.     \n",
    "In order to have stationarity we must have $|\\phi|<1$.  A small $\\kappa$ makes $\\phi \\approx 1$ and the process becomes similar to a unit root.  \n",
    "\n",
    "From the last expression, we see that also the size of $\\Delta t$ matters. \n",
    "When $\\Delta t \\to 0$ then $\\phi \\to 1$.     \n",
    "Choosing bigger value of $N$, may create problems in the detection of stationarity.      \n",
    "This is a consequence of the fact that **for short time scales, a mean-reverting process is indistinguishable from a random walk** (remember that in an autoregressive model when $|\\phi|=1$ the process is unit root)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec1.3'></a>\n",
    "## A digression on the Variance Gamma (VG) process\n",
    "\n",
    "Above I plotted the log-returns histogram together with some fitted distributions: the normal, the Student-t and the VG distributions.     \n",
    "You may ask yourself why I decided to include the VG distribution in the plot. If you look carefully, you can see that it fits the data really good!\n",
    "\n",
    "If you need to review the VG process, have a look at the notebook **1.5**.    \n",
    "Important to know, is that the process is obtained by Brownian subordination (i.e. the time $t$ in the Brownian motion is assumed to be a gamma process) and is defined as: \n",
    "\n",
    "$$ X_{t} = \\theta T_t + \\sigma W_{T_t} $$ \n",
    "\n",
    "where $W_{T_t} \\sim \\mathcal{N}(0,T_t)$ and $T_t \\sim \\Gamma(\\text{mean}=t, \\text{var}=\\kappa t)$.    \n",
    "I'm using the same letters $(\\theta, \\sigma, \\kappa)$ used for the Heston parameters, but remember that they have a different meaning: $\\theta$ and $\\sigma$ are the drift and std dev of the Brownian motion, and $\\kappa$ is the variance coefficient of the Gamma process.\n",
    "\n",
    "Alright,     \n",
    "let us try to answer the following three questions:\n",
    "\n",
    "1) How good is the VG fit?     \n",
    "2) How can we measure the quality of the fit?    \n",
    "3) Why the VG process among many others?    \n",
    "\n",
    "In order to answer the first two questions, let us define the Empirical-Cumulative-Distribution-Function [ECDF](https://en.wikipedia.org/wiki/Empirical_distribution_function):\n",
    "\n",
    "$$ \\hat F_n(x) = \\frac{1}{n} \\sum_{i=1}^{n} \\mathbb{1}_{X_i \\leq x} $$\n",
    "\n",
    "Unlike the histogram, the ECDF had the advantage that it does not depend on the number of bins.     \n",
    "We can compare the ECDF with the **Normal**, **Student-t** and **VG** theoretical cumulative distributions. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ECDF(data):\n",
    "    \"\"\" ECDF \"\"\"\n",
    "    x = np.sort(data)\n",
    "    n = x.size\n",
    "    y = np.arange(1, n+1) / n\n",
    "    return x, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "xx, yy = ECDF(ret_log)\n",
    "VG_cdf = np.array([ quad(VG_pdf, -1, i, args=(dt, VG.c, VG.theta, VG.sigma, VG.kappa))[0] for i in xx])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,5))\n",
    "plt.plot(xx, yy, color=\"darkslategray\", label=\"ECDF\")\n",
    "plt.plot(xx, ss.norm.cdf(xx, loc=mean_log, scale=std_log), color=\"green\", label=\"Normal CDF\" )\n",
    "plt.plot(xx, ss.t.cdf(xx, loc=params[1], scale=params[2], df=params[0]), color=\"blue\",\n",
    "         label=\"Stud-t, df={}\".format(params[0].round(2) ))\n",
    "plt.plot(xx, VG_cdf, label=\"VG CDF\", color=\"darkorange\" )\n",
    "plt.title(\"Comparison of Cumulative functions\"); plt.legend(); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the plot above, we can understand better which distribution fits better the data.    \n",
    "\n",
    "In order to have a quantitative measure of the goodness of fit, we can calculate the Euclidean distance between the theoretical and the empirical CDFs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance VG-ECDF:  0.14036719864722175\n",
      "Distance Student-t-ECDF:  0.34203476140854494\n",
      "Distance Normal-ECDF:  1.9583261648228154\n"
     ]
    }
   ],
   "source": [
    "print(\"Distance VG-ECDF: \", np.linalg.norm(VG_cdf-yy, ord=2) )\n",
    "print(\"Distance Student-t-ECDF: \", np.linalg.norm(\n",
    "                        ss.t.cdf(xx, loc=params[1], scale=params[2], df=params[0]) - yy, ord=2) )\n",
    "print(\"Distance Normal-ECDF: \", np.linalg.norm(ss.norm.cdf(xx, loc=mean_log, scale=std_log) - yy, ord=2) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Now we have the confirmation that the VG distribution works very well!!\n",
    "\n",
    "Ok, but are there any theoretical motivations?\n",
    "\n",
    "The answer is **yes**!  \n",
    "\n",
    "1) The variance of the Heston process follows the CIR process. I introduced the CIR process in the notebook **1.2**, where we saw that the conditional distribution of the process is a non-central chi-squared distribution. However, as time becomes large, the asymptotic distribution tends to the Gamma distribution:\n",
    "\n",
    "$$ f(v; \\alpha, \\beta ) = \\frac{\\beta^{\\alpha}}{\\Gamma(\\alpha)} v^{\\alpha-1} e^{-\\beta v} $$\n",
    "where $\\alpha = \\frac{2 \\theta \\kappa}{\\sigma^2}$ and $\\beta= \\frac{2 \\kappa}{\\sigma^2}$.\n",
    "\n",
    "2) In the VG process $X_{t} = \\theta T_t + \\sigma W_{T_t}$, the variance of the Brownian motion is Gamma distributed. I will use an heuristic Brownian approximation.    \n",
    "Since $\\mathbb{E}[X_t] = \\theta t$ and $Var[X_{t}] = (\\sigma^2 + \\theta^2 \\kappa) t$, we can define $\\sigma^2_{VG} = \\sigma^2 + \\theta^2 \\kappa$ and write: \n",
    "\n",
    "$$ X_{t} \\approx \\theta t + \\sigma_{VG} W_{T_t} $$ \n",
    "\n",
    "where, by the law of total variance, $Var \\big[ W_{T_t} \\big] = t$. The approximated model has same mean and same variance of the original VG process.   \n",
    "\n",
    "The process $\\sigma_{VG} W_{T_t}$ is known as the **symmetric Variance Gamma** process (the parameter $\\theta$ is the responsible for the skewness, if $\\theta=0$ the density is symmetric).     \n",
    "The distribution of the approximated process can be obtained from `VG_pdf`, the VG distribution $f^{VG}(x; t, c, \\theta, \\sigma, \\kappa)$, by setting the parameters \n",
    "\n",
    "$$ c= c+\\theta t \\quad \\theta=0 \\quad \\sigma=\\sigma_{VG} \\quad \\kappa=\\kappa $$ \n",
    "\n",
    "In the [plot above](#hist), we plotted both the VG and approximated VG densities. \n",
    "It is very hard to distinguish them. **In this case the approximation is very good!** \n",
    "\n",
    "The conditional variance of the symmetric VG is: \n",
    "\n",
    "$$ Var \\big[ \\sigma_{VG} W_{T_t} \\,\\big|\\, T_t \\big] \\,=\\, \\sigma^2_{VG} T_t \\,\\sim \\, \\Gamma \\big( \\text{shape=}\\frac{t}{\\kappa}, \\, \\text{scale=} \\sigma^2_{VG} \\big) $$ \n",
    "\n",
    "Therefore...      \n",
    "In both cases 1) and 2), the variance is described by a Gamma distribution.   \n",
    "Let us plot the two Gammas, together with a Gamma distribution fitted from the data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "params2 = ss.gamma.fit(V , floc=0)       # fit from data\n",
    "beta = 2*kappa/sigma**2\n",
    "alpha = 2*kappa*theta/sigma**2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "vg_path = VG.path(T=T, N=N)[0]           # VG path        \n",
    "vg_ret = vg_path[1:] - vg_path[:-1]      # VG increments "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,8));  gs = gridspec.GridSpec(2, 2, height_ratios=[4,3])\n",
    "gs00 = gs[1,:].subgridspec(1, 3, width_ratios=[1,3,1])\n",
    "ax1 = fig.add_subplot(gs[0, 0]); ax2 = fig.add_subplot(gs00[0,1]); ax3 = fig.add_subplot(gs[0, 1])\n",
    "xxx = np.linspace(V.min(),V.max(), 100)\n",
    "xxxx, yyyy = ECDF(V)\n",
    "ax1.plot(xxx, ss.gamma.pdf(xxx, a=params2[0], loc=params2[1], scale=params2[2]), color=\"darkorange\",\n",
    "         label=\"Fitted from data\"); ax1.set_title(\"Gamma densities. Histogram of the Variance CIR process\") \n",
    "ax1.plot(xxx, ss.gamma.pdf(xxx, a=dt/VG.kappa, scale=VG.var ), color=\"palevioletred\", label=\"Variance of the VG\")\n",
    "ax1.plot(xxx, ss.gamma.pdf(xxx, a=alpha, scale=1/beta ), color=\"forestgreen\", label=\"CIR asymptotic\")\n",
    "ax1.hist(V, density=True, bins=100, facecolor=\"LightBlue\", label=\"Variance\"); ax1.legend()\n",
    "ax2.plot(T_vec[1:], vg_ret)\n",
    "ax2.plot(T_vec[1:], (VG.mean*dt + np.sqrt(VG.var*dt) )*np.ones(N-1), label=\"1 std dev\", color=\"black\" )\n",
    "ax2.plot(T_vec[1:], (VG.mean*dt - np.sqrt(VG.var*dt) )*np.ones(N-1), color=\"black\" )\n",
    "ax2.plot(T_vec[1:], VG.mean*dt*np.ones(N-1), color=\"orange\", label=\"mean\" ) \n",
    "ax2.set_xlabel(\"Time\"); ax2.legend(); ax2.set_title(\"VG increments with parameters from Heston logreturns\");\n",
    "ax3.plot(xxxx, yyyy, color=\"darkslategray\", label=\"ECDF\")\n",
    "ax3.plot(xxxx, ss.gamma.cdf(xxxx, a=dt/VG.kappa, scale=VG.var ), color=\"palevioletred\", label=\"Variance of the VG\")\n",
    "ax3.plot(xxxx, ss.gamma.cdf(xxxx, a=alpha, scale=1/beta ), color=\"forestgreen\", label=\"CIR asymptotic\")\n",
    "ax3.plot(xxxx, ss.gamma.cdf(xxxx, a=params2[0], loc=params2[1], scale=params2[2]), color=\"darkorange\",\n",
    "         label=\"Fitted from data\")\n",
    "ax3.set_title(\"Comparison of Cumulative functions\"); ax3.legend(); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- The first plot shows the two theoretical Gammas obtained from the VG and CIR models. It also shows a Gamma distribution with parameters fitted from the data.     \n",
    "- The second plot compares the cumulative density functions.\n",
    "- In the third plot, you can see the simulated VG increments (with parameters fitted from the Heston log-returns).    \n",
    "\n",
    "I decided to plot the VG dynamics because it is important to understand that,\n",
    "although the VG density is very good to describe the empirical log-returns density, **the VG process is NOT able to describe the statistical feature of the Heston process i.e. volatility clusters!!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Distance: Gamma_fitted - ECDF:  0.8300503439368914\n",
      "Distance: Gamma_VG - ECDF:  1.9777785749394166\n",
      "Distance: Gamma_CIR - ECDF:  1.0003085960032345\n"
     ]
    }
   ],
   "source": [
    "print(\"Distance: Gamma_fitted - ECDF: \", np.linalg.norm(  \n",
    "            ss.gamma.cdf(xxxx, a=params2[0], loc=params2[1], scale=params2[2]) -yyyy, ord=2) )\n",
    "print(\"Distance: Gamma_VG - ECDF: \", np.linalg.norm(  \n",
    "            ss.gamma.cdf(xxxx, a=dt/VG.kappa, scale=VG.var ) -yyyy, ord=2) )\n",
    "print(\"Distance: Gamma_CIR - ECDF: \", np.linalg.norm(\n",
    "            ss.gamma.cdf(xxxx, a=alpha, scale=1/beta ) - yyyy, ord=2) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Important: The plots above depend on the initial choice of the parameters $\\rho$, $\\kappa$ and $\\sigma$.\n",
    "\n",
    "If you try to modify the parameters, for instance, $\\rho=-0.3$, $\\kappa = 15$ and $\\sigma = 1$, you will find out that the CIR-asymptotic-Gamma distribution is a much better fit than the VG-Gamma distribution.\n",
    "Other parameters can imply the opposite.\n",
    "\n",
    "#### Conclusive comment:\n",
    "\n",
    "For any choice of the CIR parameters, the VG distribution is always better than the Normal or Student-t, when fitting the log-returns!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec2'></a>\n",
    "# GARCH(1,1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the previous section we obtained the stochastic model for the returns: $ R_{t} = \\sqrt{v_{t-1}}\\, \\epsilon_{t} $ as a result of the explicit discretization of stock process SDE.   \n",
    "However, the most common discrete time models, prefer to consider the expression:\n",
    "\n",
    "$$ R_{t} = \\sqrt{v_t}\\, \\epsilon_{t} $$\n",
    "\n",
    "where $v_t$ usually can be deterministic or stochastic. Usually, in deterministic models such as ARCH and GARCH the variance $v_t$ is a function of variables at previous times.\n",
    "\n",
    "**The difficult task is to estimate the variance value $v_t$**.    \n",
    "Let us try two common methods:\n",
    "\n",
    "- 1) Let us consider the [GARCH(1,1)](https://en.wikipedia.org/wiki/Autoregressive_conditional_heteroskedasticity#GARCH) model:\n",
    "\n",
    "$$ v_t = \\omega + \\alpha \\, R_{t-1}^2 + \\beta \\, v_{t-1}  $$\n",
    "\n",
    "where $\\omega = \\gamma V_L$. The parameter $V_L$ is the long term variance (unconditional variance).   \n",
    "The weights must satisfy: $\\alpha, \\beta >0$, $\\gamma \\geq 0$ and $\\alpha + \\beta + \\gamma = 1$. \n",
    "After having fitted the parameters $\\omega$, $\\alpha$ and $\\beta$, it is possible to compute the other parameters as:\n",
    "\n",
    "$$ \\gamma = 1-\\alpha-\\beta \\quad \\text{and} \\quad V_L = \\frac{\\omega}{\\gamma}. $$\n",
    "\n",
    "If $\\alpha + \\beta = 1$ the unconditional variance $V_L$ is not well defined.\n",
    "And this means that the GARCH process is not stationary anymore i.e. it is unit root.\n",
    "\n",
    "Usually the GARCH(1,1) is sufficient to capture the volatility clustering in the data. There is no need for an higher order GARCH(p,q) with $p,q>1$.\n",
    "\n",
    "\n",
    "- 2) Another possibility is to compute the **rolling variance**. Using a time window of $m$ points, we can compute:\n",
    "\n",
    "$$ v_t = \\frac{1}{m} \\sum_{i=0}^{m-1} R_{t-i}^2 $$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec2.1'></a>\n",
    "### Computing the GARCH with the arch library\n",
    "\n",
    "The [arch library](https://arch.readthedocs.io/en/latest/univariate/introduction.html) gives the possibility to estimate the mean $\\mu$ as well:\n",
    "\n",
    "$$ R_{t} = \\mu + \\sqrt{v_t}\\, \\epsilon_{t} $$\n",
    "\n",
    "But we don't care about it, and we detrend the series: "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Comments on the output below:\n",
    "\n",
    "- I chose a quite big value `train_size = 1500`. If we want to compare this number with realistic data, this corresponds to 6 years of daily data.     \n",
    "The reason of this big number is that in order to compute the parameter $\\omega$ (proportional to the long term variance) with a good precision (small standard error), we need a lot of data.\n",
    "\n",
    "\n",
    "- If you set `mean=\"constant\"` the parameter $\\mu$ will be estimated. You will find a $\\mu$ very close to zero, or   a big *p-value*.\n",
    "\n",
    "\n",
    "- You can try to change the GARCH values of `p` and `q`. However, in this example, $p=q=1$ produce the **smallest** [AIC](https://en.wikipedia.org/wiki/Akaike_information_criterion) i.e. provide the best model. \n",
    "\n",
    "\n",
    "- The optimizer requires to rescale the data in some cases, see discussion on [stackoverflow](https://stackoverflow.com/questions/11155721/positive-directional-derivative-for-linesearch)\n",
    "It is possible to set `rescale=True` to automatically rescale the data, but I prefer to do it manually by introducting a `scale_factor=1/dt`.\n",
    "\n",
    "\n",
    "- If you try to set `dist=\"StudentsT\"`, you will obtain a quite big value of estimated degrees of freedom $\\nu>30$, confirming that the data was generated by a Gaussian error.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_size = 1500\n",
    "train = ret_log[:train_size]\n",
    "train = train - train.mean()            # detrend the series   \n",
    "test = ret_log[train_size:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alpha + beta =  0.9928\n",
      "The parameter gamma= 0.0072\n",
      "scaled omega =  2.8472e-06\n",
      "The long term variance is:  0.0991\n",
      "\n",
      "                       Zero Mean - GARCH Model Results                        \n",
      "==============================================================================\n",
      "Dep. Variable:                      y   R-squared:                       0.000\n",
      "Mean Model:                 Zero Mean   Adj. R-squared:                  0.001\n",
      "Vol Model:                      GARCH   Log-Likelihood:               -5961.62\n",
      "Distribution:                  Normal   AIC:                           11929.2\n",
      "Method:            Maximum Likelihood   BIC:                           11945.2\n",
      "                                        No. Observations:                 1500\n",
      "Date:                Thu, Nov 19 2020   Df Residuals:                     1497\n",
      "Time:                        18:06:35   Df Model:                            3\n",
      "                             Volatility Model                             \n",
      "==========================================================================\n",
      "                 coef    std err          t      P>|t|    95.0% Conf. Int.\n",
      "--------------------------------------------------------------------------\n",
      "omega          2.8472      1.007      2.828  4.682e-03   [  0.874,  4.820]\n",
      "alpha[1]       0.1222  2.084e-02      5.864  4.524e-09 [8.136e-02,  0.163]\n",
      "beta[1]        0.8706  1.877e-02     46.372      0.000   [  0.834,  0.907]\n",
      "==========================================================================\n",
      "\n",
      "Covariance estimator: robust\n"
     ]
    }
   ],
   "source": [
    "scale_factor = 1000\n",
    "am = arch_model(scale_factor*train, mean='zero', vol='GARCH', p=1, q=1, rescale=False)\n",
    "res = am.fit(disp='off')  \n",
    "print(\"alpha + beta = \", (res.params[1] + res.params[2]).round(4) )\n",
    "print(\"The parameter gamma=\", (1 - (res.params[1] + res.params[2]) ).round(4) )\n",
    "print(\"scaled omega = \", (1/scale_factor**2) * res.params[0].round(4) )\n",
    "arch_long_var = (1/scale_factor**2 ) * res.params[0] / (1 - (res.params[1] + res.params[2]) )\n",
    "print(\"The long term variance is: \", (arch_long_var/dt).round(4))\n",
    "print();  print(res.summary() )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If $\\alpha + \\beta \\approx 1$, as is typically the case, then the model is not very sensitive to the term $V_L$ for short horizons, however, $V_L$ becomes important for longer horizons."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec2.2'></a>\n",
    "### Computing the GARCH from scratch\n",
    "\n",
    "\n",
    "I implemented the GARCH(1,1) class in [Processes.py](./functions/Processes.py).    \n",
    "The class contains the methods:\n",
    "- `path`:  It uses a Monte Carlo simulation to generate a GARCH(1,1) process.\n",
    "- `log_likelihood`: It computes the log-likelihood function, and optionally, it returns the last variance value. \n",
    "- `fit_from_data`: It fits the GARCH(1,1) parameters from a time series.\n",
    "- `generate_var`: It generates the variance process from a series of returns.\n",
    "\n",
    "Let us create a garch process and fit the parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully\n",
      "         Params        SE         P-val  95% CI lower  95% CI upper\n",
      "omega  0.000011  0.000011  1.564658e-01     -0.000010      0.000032\n",
      "alpha  0.171224  0.060724  2.403255e-03      0.052208      0.290240\n",
      "beta   0.785951  0.102420  8.350816e-15      0.585210      0.986691\n",
      "\n",
      "gamma =  0.0428\n",
      "The long term variance is:  0.0629\n"
     ]
    }
   ],
   "source": [
    "garch = GARCH()\n",
    "garch.fit_from_data(train, disp=True)\n",
    "print(); print(\"gamma = \", garch.gamma.round(4)); print(\"The long term variance is: \", (garch.VL/dt).round(4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### The output of my algorithm is a little different from that of the arch library: \n",
    "\n",
    "- I didn't check the settings in the `arch library`. I only know we are both using `scipy.optimize.minimize` with [SLSQP](https://docs.scipy.org/doc/scipy/reference/optimize.minimize-slsqp.html) to find the minimum of the negative log-likelihood. \n",
    "\n",
    "I used the formula for the (Gaussian) log-likelihood:\n",
    "\n",
    "$$ \\log L(\\omega, \\alpha, \\beta; R) = \\frac{1}{2} \\sum_{i=1}^N \\biggl[ -\\log{2\\pi} -\\log v_i - \\frac{R_i^2}{v_i} \\biggr] $$\n",
    "\n",
    "where the variance $v_i$ is calculated ricursively, and I assumed as initial value $v_{i=0} = R^2_{i=0}$.\n",
    "\n",
    "- The arch library uses a robust method for the estimation of the covariance matrix of the parameters. The provided standard errors are thus robust.     \n",
    "Instead, I simply implemented the formula:\n",
    "\n",
    "$$ \\text{COV}\\bigg[\\hat\\omega_{ML}, \\hat\\alpha_{ML}, \\hat\\beta_{ML}\\bigg] = \\bigg[\\mathbf{I}\\big(\\hat\\omega_{ML}, \\hat\\alpha_{ML}, \\hat\\beta_{ML} \\big)\\bigg]^{-1} $$\n",
    "\n",
    "where \n",
    "\n",
    "$$\\mathbf{I}(\\theta) = - \\frac{\\partial^2}{\\partial \\theta_i \\, \\partial \\theta_j} \\log L(\\theta) \n",
    "\\quad \\quad \\text{and} \\quad \\quad \\theta=(\\omega, \\alpha, \\beta)$$\n",
    "\n",
    "is the [Fisher Information matrix](https://en.wikipedia.org/wiki/Fisher_information). The *observed Fisher information matrix* is simply $\\mathbf{I}(\\hat \\theta_{ML})$.\n",
    "\n",
    "The inverse of the (negative) Hessian of the log-likelihood is an estimator of the asymptotic covariance matrix. Hence, the square roots of the diagonal elements of covariance matrix are estimators of the standard errors.    \n",
    "I used `statsmodels.tools.numdiff.approx_hess` for the numerical computation of the Hessian.\n",
    "\n",
    "We can check which set of parameters is better:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Log-Likelihood function of my implementation =  4382.63\n"
     ]
    }
   ],
   "source": [
    "log_lik, _ = garch.log_likelihood(train, last_var=True)\n",
    "print(\"Log-Likelihood function of my implementation = \", log_lik.round(2) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Log-Likelihood function of arch parameters =  4395.54\n"
     ]
    }
   ],
   "source": [
    "garch_from_arch = GARCH(VL=arch_long_var, alpha=res.params[1], beta=res.params[2])\n",
    "log_lik_arch, last_var = garch_from_arch.log_likelihood(train, last_var=True)\n",
    "print(\"Log-Likelihood function of arch parameters = \", log_lik_arch.round(2) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### It seems that the ARCH implementation provides better parameters in terms of maximum likelihood.\n",
    "\n",
    "I compared my implementation with ARCH on several simulated dataset, and the results are always very similar. Of course, as expected, the ARCH is more accurate, as we can see from the results above.\n",
    "\n",
    "We can use the parameters fitted from the ARCH method `fit()` to track the variance, using the GARCH recursion algorithm `generate_var`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "var_train = garch_from_arch.generate_var( R=train[1:], R0=train[0], var0=train[0]**2 )\n",
    "var_test = garch_from_arch.generate_var( R=test, R0=train[-1], var0=last_var )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,3))\n",
    "ax1 = fig.add_subplot(121); ax2 = fig.add_subplot(122)\n",
    "#ax1.plot((1/(dt*scale_factor**2) ) *res.conditional_volatility**2)    # ARCH method equivalent to generate_var\n",
    "ax1.plot(V[1:train_size], label=\"Heston variance\"); ax2.plot(V[1+train_size:], label=\"Heston variance\")\n",
    "ax1.plot(var_train/dt, label=\"GARCH var process\", color='sandybrown', linestyle='--')\n",
    "ax2.plot(var_test/dt, label=\"GARCH var process\", color='sandybrown', linestyle='--')\n",
    "ax1.set_title(\"In sample tracking: using train data\"); ax2.set_title(\"Out of sample tracking: using test data\")\n",
    "ax1.legend();ax2.legend(); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec2.3'></a>\n",
    "### Rolling Variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "window = 20\n",
    "ret_df = pd.Series(ret_log, index=T_vec[1:])\n",
    "roll_var = ret_df.rolling(window).var(ddof=0) / dt   # MLE estimate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(14,4))\n",
    "plt.plot( V[train_size+1:] , label=\"Heston variance process\", linewidth=2, color=\"steelblue\" )\n",
    "plt.plot( var_test/dt, label=\"GARCH variance process\", color='lightcoral', linestyle='--' )\n",
    "plt.plot( roll_var.values[train_size:], label=\"Rolling Variance\", linestyle='--', alpha=1, color=\"limegreen\")\n",
    "plt.title(\"Out of sample comparison: GARCH vs Rolling\")\n",
    "plt.legend(); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec3'></a>\n",
    "# Kalman filter\n",
    "\n",
    "In this section I'm going to present the model initially proposed by Taylor [2], with the linearization and estimation method described in Harvey, Ruiz and Shephard, [3], [4] and [5]."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Model linearization:\n",
    "\n",
    "Let us consider the model for the returns defined before:\n",
    "\n",
    "$$ R_{t} = \\sqrt{v_t}\\, e_{t}  \\quad \\text{with} \\quad e_{t} \\sim \\mathcal{N}(0,1).  $$\n",
    "\n",
    "It is quite useful to introduce an additional scale parameter $\\bar \\sigma$, such that the model becomes: \n",
    "\n",
    "$$ R_{t} = \\bar \\sigma \\sqrt{v_t}\\, e_{t}  \\quad \\text{with} \\quad e_{t} \\sim \\mathcal{N}(0,1).  $$\n",
    "\n",
    "This model is multiplicative. The first thing that comes to mind is to take the log transform to make it linear!!     \n",
    "If you remember, already in the notebook **1.4** we found useful to define the log-variance $h_t := \\log v_t$.\n",
    "\n",
    "In order to remove the square root, we can square the equation on both sides, and then take the logarithm:\n",
    "\n",
    "$$ \\begin{aligned}\n",
    "\\log R_{t}^2 &= \\log \\big( \\bar \\sigma^2 \\, v_t \\, e_{t}^2 \\big) \\\\\n",
    "             &= \\log \\bar \\sigma^2 \\,+ \\log v_t \\,+ \\log e_{t}^2 \\; \\pm \\; \\mathbb{E}\\big[\\log e_{t}^2 \\big] \\\\\n",
    "             &= \\log \\bar \\sigma^2 \\,+ \\mathbb{E}\\big[\\log e_{t}^2 \\big] + h_t + \\epsilon_t \n",
    "\\end{aligned} $$\n",
    "\n",
    "Where we called $\\epsilon_t := \\log e_{t}^2 - \\mathbb{E}\\big[\\log e_{t}^2 \\big]$.       \n",
    "\n",
    "We want to create a state space model with an hidden state variable (see notebook **5.1** for a review of the general theory).\n",
    "The hidden variable in this model is the log-variance. We can assume it follows an autoregressive process: \n",
    "\n",
    "$$ h_t = \\phi h_{t-1} + \\eta_t \\quad \\text{with} \\quad \\eta_{t} \\sim \\mathcal{N}(0,\\sigma_{\\eta}^2), $$\n",
    "\n",
    "with $|\\phi|\\leq 1$.     \n",
    "However, the resulting system (state equation in $\\log v_t$ and measurement equation in $\\log R_t^2$) is NOT a linear Gaussian state space model.     \n",
    "The reason is that the random variable \n",
    "\n",
    "$$\\log e_{t}^2 \\sim Log \\chi^2_1$$ \n",
    "\n",
    "is not Gaussian, but follows the Log-Chi-Squared distribution with 1 degree of freedom.     \n",
    "It satisfies $\\mathbb{E}\\big[\\log e_{t}^2 \\big] \\approx -1.27$ and\n",
    "$Var\\big[\\log e_{t}^2 \\big] = \\frac{\\pi^2}{2}$.\n",
    "\n",
    "In order to make the system a linear Gaussian state space model, we can approximate \n",
    "\n",
    "$$ \\epsilon_t \\sim \\mathcal{N}\\bigg(0,\\frac{\\pi^2}{2} \\bigg). $$\n",
    "\n",
    "Let us check if this approximation is good:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "def log_chi2(x):\n",
    "    \"\"\" Log-Chi-Squared density \"\"\"\n",
    "    return 1/np.sqrt(2*np.pi) * np.exp( x/2 - np.exp(x)/2 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean of the Log-Chi-Squared -1.2704\n",
      "Variance of the Log-Chi-Squared 4.9348\n"
     ]
    }
   ],
   "source": [
    "mean_chi2 = quad(lambda x: x*log_chi2(x), -30, 10)[0]\n",
    "var_chi2 = quad(lambda x: ((x-mean_chi2)**2)*log_chi2(x), -50, 10)[0]\n",
    "print(\"Mean of the Log-Chi-Squared\", round(mean_chi2,4) )\n",
    "print(\"Variance of the Log-Chi-Squared\", round(var_chi2,4) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,3)); x = np.linspace(-15, 5, 200)\n",
    "plt.plot(x, ss.norm.pdf(x, loc=mean_chi2, scale=np.sqrt(var_chi2)), 'b-', lw=2, alpha=0.6, label='Normal pdf')\n",
    "plt.plot(x, log_chi2(x), 'r-', lw=2, alpha=0.6, label='Log-Chi-Squared pdf')\n",
    "plt.title(\"Approximation:  Normal ~ Log-Chi-Squared\"); plt.legend(); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well... it doesn't seem so good at first sight.      \n",
    "But it is proved in many articles (see references in [3] and [4]) that this approximation is good enough to produce a nice output.      \n",
    "Indeed, this method is quite used in practice."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec3.1'></a>\n",
    "### Gaussian linear state space model:\n",
    "\n",
    "**State equation:**\n",
    "\n",
    "$$ h_k = \\phi h_{k-1} + \\eta_k \\quad \\text{with} \\quad \\eta_{k} \\sim \\mathcal{N}(0,\\sigma_{\\eta}^2). $$\n",
    "\n",
    "**Measurment equation:**\n",
    "\n",
    "$$ \\bigg( \\log R_{k}^2 + 1.27 -\\log \\bar \\sigma^2 \\bigg)= \\; h_k + \\epsilon_k \\quad \\text{with} \\quad \\epsilon_k \\sim \\mathcal{N}\\bigg(0,\\frac{\\pi^2}{2} \\bigg).$$\n",
    "\n",
    "### Kalman filter:\n",
    "\n",
    "Let us identify the Kalman filter elements. You can find them in the notebook **5.1** or in the [wiki page](https://en.wikipedia.org/wiki/Kalman_filter#Details).\n",
    "\n",
    "In this model $F_k = \\phi$ and $ H_k=1$ are constant. They do not depend on $k$.    \n",
    "\n",
    "##### Predict step:\n",
    "$$ \\hat h_{k \\mid k-1} = \\phi\\, \\hat h_{k-1 \\mid k-1} \\quad \\quad \\text{and} \\quad \\quad  P_{k \\mid k-1} = \\phi^2 \\, P_{k-1 \\mid k-1} + \\sigma_{\\eta}^2. $$\n",
    "\n",
    "##### Auxiliary variables:\n",
    "$$ \n",
    "\\begin{aligned}\n",
    "\\tilde y_k &= \\log R_{k}^2 + 1.27 -\\log \\bar \\sigma^2 \\, - \\hat h_{k \\mid k-1} &\\quad \\quad \\text{(pre-fit residual)} \\\\\n",
    "S_k &= P_{k \\mid k-1} + \\frac{\\pi^2}{2} &\\quad \\quad \\text{(conditional innovation covariance)} \\\\\n",
    "K_k &= \\frac{P_{k \\mid k-1}}{S_k} &\\quad \\quad \\text{(Kalman Gain)}\n",
    "\\end{aligned}\n",
    "$$\n",
    "\n",
    "##### Update step:\n",
    "$$ \\hat h_{k \\mid k} = \\hat h_{k \\mid k-1} + K_k \\, \\tilde y_k  \\quad \\text{and} \\quad \n",
    "P_{k \\mid k} = P_{k \\mid k-1} \\biggl( 1- K_k \\biggr)\n",
    "$$\n",
    "\n",
    "In order to familiarize with these formulas, let us compute the conditional expectation and variance of the innovations i.e. the new measurements:\n",
    "\n",
    "$$ \\mathbb{E}\\bigg[ \\log R_k^2 \\, \\bigg|\\, \\hat h_{k-1 \\mid k-1} \\bigg] = \\, -1.27 \\,+ \\log \\bar \\sigma^2 \\, + \\hat h_{k \\mid k-1} $$\n",
    "\n",
    "$$ \\text{Var} \\bigg[ \\log R_k^2 \\, \\bigg|\\, \\hat h_{k-1 \\mid k-1} \\bigg] = \\, P_{k \\mid k-1} + \\frac{\\pi^2}{2} \\; = S_k $$\n",
    "\n",
    "\n",
    "### Log-likelihood\n",
    "\n",
    "The parameters $(\\phi, \\sigma_{\\eta},\\bar \\sigma)$ can be estimated using the QML method (Quasi-Maximum-Likelihood), where the \"Quasi\" refers to the Gaussian approximation of $\\epsilon_k$.     \n",
    "The log-likelihood function is:\n",
    "\n",
    "$$ \\log L \\big( \\phi, \\sigma_{\\eta},\\bar \\sigma \\mid R_k, R_{k-1}, ..., R_1, R_0 \\big) = -\\frac{1}{2} \n",
    "\\sum_{k=1}^N \\biggl( \\log 2\\pi + \\log S_k + \\frac{\\tilde y_k^2}{S_k}  \\biggr)\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "h0 = np.log(train.var())   # initial value for the log-variance\n",
    "P0 = 100                   # initial variance of the log-variance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above I chose an initial hidden state $h_0$ equal to the logarithm of the variance computed in the training set.   \n",
    "Since we have no knowledge of the true value of $h_0$, it is better to select a huge value of the initial error $P_0 = 100$.\n",
    "\n",
    "In the function below, I indicate $\\bar \\sigma$ with `scale`, and the residuals $\\tilde y_k$ with `r`. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='sec3.2'></a>\n",
    "## Algorithm implementation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Kalman(data, h0, P0, phi, var_eta, scale ):\n",
    "    \"\"\" One dimensional Kalman filter algorithm \"\"\"\n",
    "    \n",
    "    Y = np.log(data**2)             # take the log of squared data\n",
    "    N = len(Y)                       \n",
    "    hs = np.zeros_like(Y)           # Initialization\n",
    "    Ps = np.zeros_like(Y)\n",
    "        \n",
    "    Y = Y + 1.27 - np.log(scale**2)       # redefine Y. scale corresponds to \\bar{\\sigma} \n",
    "    h = h0; P = P0                        # initial values of h and P\n",
    "    log_2pi = np.log(2 * np.pi); loglikelihood = 0      # initialize log-likelihood\n",
    "    \n",
    "    for k in range(N):\n",
    "        # Prediction step\n",
    "        h_p = phi * h                   # predicted h\n",
    "        P_p = phi**2 * P + var_eta      # predicted P\n",
    "\n",
    "        # auxiliary variables\n",
    "        r = Y[k] - h_p                 # residual\n",
    "        S = P_p + 0.5 * np.pi**2\n",
    "        KG = P_p / S                   # Kalman Gain\n",
    "        \n",
    "        # Update step\n",
    "        h = h_p + KG * r\n",
    "        P = P_p * (1 - KG)\n",
    "\n",
    "        loglikelihood += -0.5 * ( log_2pi + np.log(S) + (r**2/S) )      \n",
    "        hs[k] = h; Ps[k] = P\n",
    "        \n",
    "    return hs, Ps, loglikelihood"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The log-likelihood function may have multiple local minima. For this reason, remember to repeat the minimization several times with different initial conditions. (For instance, if you try `x0=[0.1, 0.5, 1]` you will get different locally optimal values)\n",
    "\n",
    "##### Parameter estimation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      fun: 3374.975321609764\n",
      " hess_inv: <3x3 LbfgsInvHessProduct with dtype=float64>\n",
      "      jac: array([-0.0041382 , -0.00095497, -0.01996341])\n",
      "  message: b'CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH'\n",
      "     nfev: 136\n",
      "      nit: 18\n",
      "     njev: 34\n",
      "   status: 0\n",
      "  success: True\n",
      "        x: array([0.97760755, 0.0371697 , 0.01228061])\n"
     ]
    }
   ],
   "source": [
    "def minus_likelihood(c):\n",
    "    \"\"\" Returns the negative log-likelihood \"\"\"\n",
    "    _, _, loglik = Kalman(train, h0, P0, c[0], c[1], c[2])\n",
    "    return -loglik\n",
    "        \n",
    "result = minimize(minus_likelihood, x0=[0.1, 1, 1], \n",
    "                      method='L-BFGS-B', bounds=[[-1,1],[1e-15,None],[1e-15,None]], tol=1e-8)\n",
    "kalman_params = result.x\n",
    "print(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "hs, Ps, _ = Kalman(train, h0, P0, *kalman_params)                  # Kalman on training set\n",
    "h_test, P_test, _ = Kalman(test, hs[-1], Ps[-1], *kalman_params)   # Kalman on test set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "phi = kalman_params[0]\n",
    "var_eta = kalman_params[1]\n",
    "scale = kalman_params[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Kalman Smoother:\n",
    "\n",
    "Let's implement the [RTS](https://en.wikipedia.org/wiki/Kalman_filter#Rauch%E2%80%93Tung%E2%80%93Striebel) smoother:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "hs_smooth = np.zeros_like(h_test)\n",
    "Ps_smooth = np.zeros_like(P_test)\n",
    "hs_smooth[-1] = h_test[-1] \n",
    "Ps_smooth[-1] = P_test[-1]\n",
    "    \n",
    "for k in range( len(h_test)-2,-1,-1):\n",
    "    C = phi * P_test[k] / (phi**2 * P_test[k] + var_eta)  \n",
    "    hs_smooth[k] = h_test[k] + C*( hs_smooth[k+1] - h_test[k]*phi )\n",
    "    Ps_smooth[k] = P_test[k] + C**2 *( Ps_smooth[k+1] - (phi**2 * P_test[k] + var_eta) )\n",
    "\n",
    "smooth_h = np.exp(hs_smooth)/dt*scale**2                     # Kalman re-transformed variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "V_kalm = np.exp(h_test)/dt*scale**2                     # Kalman re-transformed variance  \n",
    "V_up = np.exp(h_test+np.sqrt(P_test))/dt*scale**2       # error up bound \n",
    "V_down = np.exp(h_test-np.sqrt(P_test))/dt*scale**2     # error down bound    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Plots:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AwO23345bbrkFvu/jwIEDeP7556MANQxii/35z3/GV7/6VWQyGXR1dWHZsmVRgHrFFVcAAM4++2zs3Lkzetwf+tCHkEiYkKujowMbN27Exo0bcemllwIwWdY5c+bU+jQfFxigEo2yfb2HsbNrP1afuBQtqaZ6Hw4RERHRmFJK4dFHH0VTU+F50Gc/+1m87nWvwz333IPzzz+/bDOisIy2nIaGhuhr27bh+37Jda688krcdNNN6OjowJo1a9DW1oYdO3bgxhtvxJNPPolp06bhqquuKhiF0tLSUnI/uVwOH/7wh7F27VrMnz8f1113XcFtwmOJH4fWuqSLrdYay5Ytw6OPPlrxcR3vGKASjbKtR/ZASontR/di5Zwl9T4cIiIimsSqleHWy2WXXYbvfOc7+NSnPgXAlOauXr0a27dvx4oVK7BixQo8+uij2Lx5M+bPn4/+/v7othdeeCF+8pOf4FWvehVeeOEF7N69G0uXLsVTTz1V08++6KKL8Hd/93f43ve+F2VG+/r60NLSgvb2dhw6dAi///3vcdFFF1W9nzAYnTFjBgYGBnDHHXfgrW9966CP++abb8ZFF10UlfguXboUnZ2dePTRR/GSl7wEnufhhRdewLJly2p6PMcDNkkiGgOe8qGUqvdhEBEREY25b33rW1i7di1WrlyJM844AzfffDMA4Bvf+AaWL1+OVatWoampCa95zWuwcuVKJBIJrFq1Cv/+7/+OD3/4w5BSYsWKFbjyyitx2223FWROB2PbNl7/+tfj97//PV7/+tcDAFatWoUzzzwTy5Ytw/ve9z5ccMEFg97P1KlTcfXVV2PFihV485vfjDVr1gx6m/e///1YsGABVq5ciVWrVuGnP/0pUqkU7rjjDnzmM5/BqlWrsHr1avz1r3+t+fEcD0S1tHm9nHPOOTqsWSea6B7Yvg79uTRObJ+Fs+adVu/DISIioklm06ZNOP300+t9GERllXt9CiHWaa3PKXd9ZlCJxoAnvap7KIiIiIiIiAEq0ZjwpITSLPElIiIiIqqGASrRGPCkDwVmUImIiIiIqmGASjQGPOWzxJeIiIiIaBAMUInGgCc9lvgSEREREQ2CASrRKFJaQWsFXylIjpkhIiIiIqqKASrRKJJKQSkNpRV85TOLSkRERJNSa2tr9PU999yDJUuWYPfu3RWvf9111+HGG28ci0MbEWvXrsVHP/rReh/GcSFR7wMgmsykUlDB3lOpFDzpoyGRqvNREREREY2OP/3pT7jmmmtw3333YcGCBfU+nBHh+z7OOeccnHNO2bGdNMKYQSUaRVLnx8tIpeArWecjIiIiIhodDz30EK6++mrcfffdOPnkkwEA3/ve97BmzRqsWrUKf/M3f4NMJlNyu4suugif+MQncOGFF+L000/Hk08+iSuuuAJLlizBP//zP0fXe/Ob34yzzz4by5Ytwy233BJ9v7W1Ff/0T/+EVatW4fzzz8ehQ4cK7l8phUWLFqGnpyf63imnnIJDhw7hd7/7Hc477zyceeaZuOSSS6LbXnfddfjABz6Ayy67DO9+97vxwAMP4PWvfz0A4IknnsBLX/pSnHnmmXjpS1+KLVu2AABuu+02XHHFFbj88suxZMkSfPrTn45+3r333ouzzjoLq1atwsUXXwwASKfTeN/73oc1a9bgzDPPxG9+85tjefonDWZQiUaRyaCaAFVDs5MvERERjarD37tuVO531tXV79dxHLzpTW/CAw88gNNOOy36/hVXXIGrr74aAPDP//zP+MEPfoBrrrmm5PapVAoPPvggvvnNb+JNb3oT1q1bh46ODpx88sn4xCc+genTp+PWW29FR0cHstks1qxZg7/5m7/B9OnTkU6ncf755+OGG27Apz/9aXzve98rCGwty8Kb3vQm3HnnnXjve9+Lxx9/HIsWLcLs2bPxspe9DI899hiEEPj+97+Pr371q/i3f/s3AMC6devw8MMPo6mpCQ888EB0f6eddhoefPBBJBIJ3H///fjc5z6HX/7ylwCADRs2YP369WhoaMDSpUtxzTXXoLGxEVdffTUefPBBLF68GF1dXQCAG264Aa961atw6623oqenB+eeey4uueQStLS0DOt3NFkwQCUaRUrnS3x18B8RERHRZJNMJvHSl74UP/jBD/DNb34z+v7GjRvxz//8z+jp6cHAwABe/epXl739G9/4RgDAihUrsGzZMsyZMwcAcNJJJ2HPnj2YPn06vvWtb+HOO+8EAOzZswdbt27F9OnTkUqlouzm2WefjT/+8Y8l93/llVfi+uuvx3vf+1787Gc/w5VXXgkA2Lt3L6688kocOHAAruti8eLFBcfU1NRUcl+9vb14z3veg61bt0IIAc/zossuvvhitLe3AwDOOOMM7Nq1C93d3bjwwguj++7o6AAA3Hffffjtb38b7cXN5XLYvXs3Tj/99EGf78mMASrRKJIqX+ILzQwqERERja7BMp2jxbIs3H777bjkkkvwpS99CZ/73OcAAFdddRV+/etfY9WqVbjtttsKMpFxDQ0N0f2EX4f/9n0fDzzwAO6//348+uijaG5uxkUXXYRcLgfABMdCCACAbdvwfb/k/l/ykpdg27Zt6OzsxK9//esow3rNNdfgk5/8JN74xjfigQcewHXXXRfdplIm8/Of/zxe+cpX4s4778TOnTtx0UUXlTyO+LForaPji9Na45e//CWWLl1a9uccr7gHlWgUSR0r8WWASkRERJNYc3Mz7rrrLvzkJz/BD37wAwBAf38/5syZA8/z8JOf/GTY993b24tp06ahubkZmzdvxmOPPTak2wsh8Ja3vAWf/OQncfrpp2P69OnR/Z544okAgB/96Ec1H0t4m9tuu23Q67/kJS/BX/7yF+zYsQMAohLfV7/61fj2t78dnR+uX79+SI9psmIGlWgUxbv4mhJfBqhEREQ0eXV0dODee+/FhRdeiBkzZuD//J//g/POOw8LFy7EihUr0N/fP6z7vfzyy3HzzTdj5cqVWLp0Kc4///wh38eVV16JNWvWFASV1113Hd72trfhxBNPxPnnnx8FkdV8+tOfxnve8x58/etfx6te9apBrz9z5kzccsstuOKKK6CUwqxZs/DHP/4Rn//85/Hxj38cK1euhNYaixYtwl133TXkxzXZiPGY0TnnnHP02rVr630YRMdsb89hPL7rWRzoP4LFHXPx0kWrMK15Sr0Pi4iIiCaRTZs2Hff7Fmn8Kvf6FEKs01qXndvDEl+iUaS0irKmbJJERERERFQdA1SiUVTQxVdr6LBhEhERERERlWCASjSK4o2RmEElIiIiIqqOASrRKFJa5xsjsYsvEREREVFVDFCJRpHSGmFMqqHZxZeIiIiIqAoGqESjSBXMQQWYQCUiIiIiqowBKtEoUlrFynrZJImIiIgmJ9u2sXr1aixfvhxveMMb0NPTg/POOw+rV6/GggULMHPmTKxevRqrV6/Gzp07ceutt2LFihVYuXIlli9fjt/85jd1Pf7bbrsN+/fvj/69aNEiHDlypI5HdPxK1PsAiCazMDgVwmKTJCIiIpq0mpqasGHDBgDAe97zHtx00014/PHHAZjgb+3atfjOd74DANi7dy9uuOEGPPXUU2hvb8fAwAA6OzvrdejRMS5fvhxz58495vvyfR+JBMOs4WIGlWgUKa2htIIlREFHXyIiIqLJ6iUveQn27dtX8fLDhw+jra0Nra2tAIDW1lYsXry45Hq/+MUvsHz5cqxatQoXXnghABNIvvnNb8Yb3vAGLF68GN/5znfw9a9/HWeeeSbOP/98dHV1AQA2bNiA888/HytXrsRb3vIWdHd3V/z+HXfcgbVr1+Kd73wnVq9ejWw2CwD49re/jbPOOgsrVqzA5s2bAQDpdBrve9/7sGbNGpx55plR5ve2227D2972NrzhDW/AZZddNkLP5PGJoT3RKFJQUNCwhADYJImIiIhG2b0f/zgOBpnMkXLC6tW4/BvfqOm6Ukr86U9/wt/93d9VvM6qVaswe/ZsLF68GBdffDGuuOIKvOENbyi53vXXX48//OEPOPHEE9HT0xN9f+PGjVi/fj1yuRxOOeUUfOUrX8H69evxiU98Av/1X/+Fj3/843j3u9+Nb3/723jFK16BL3zhC/jiF7+Ib3zjGxW//53vfAc33ngjzjnnnOjnzJgxA0899RS++93v4sYbb8T3v/993HDDDXjVq16FW2+9FT09PTj33HNxySWXAAAeffRRPPPMM+jo6KjtiaWymEElGkU66IxkCStoksQAlYiIiCafbDaL1atXY/r06ejq6sKll15a8bq2bePee+/FHXfcgVNPPRWf+MQncN1115Vc74ILLsBVV12F733ve5BSRt9/5Stfiba2NsycORPt7e1RcLtixQrs3LkTvb296OnpwSte8QoApuT4wQcfrPj9Sq644goAwNlnn42dO3cCAO677z58+ctfxurVq3HRRRchl8th9+7dAIBLL72UwekIqCmDKoS4HMA3AdgAvq+1/nLR5e8E8JngnwMA/l5r/XQttyWazJTWUIAJUJlBJSIiolFWa6ZzpIV7UHt7e/H6178eN910Ez760Y9WvL4QAueeey7OPfdcXHrppXjve99bEqTefPPNePzxx3H33Xdj9erV0R7XhoaG6DqWZUX/tiwLvu+P2GMK79e27eh+tdb45S9/iaVLlxZc9/HHH0dLS8uI/ezj2aAZVCGEDeAmAK8BcAaAdwghzii62g4Ar9BarwTwfwDcMoTbEk1aWisg2INq/l3nAyIiIiIaRe3t7fjWt76FG2+8EZ7nlb3O/v378dRTT0X/3rBhAxYuXFhyve3bt+O8887D9ddfjxkzZmDPnj01H8O0adPw0EMPAQB+/OMf4xWveEXF7wNAW1sb+vv7B73vV7/61fj2t78dVcWtX7++pmOi2tWSQT0XwDat9YsAIIT4GYA3AXg+vILW+q+x6z8GYF6ttyWazEyTJI2EJZhBJSIiouPCmWeeiVWrVuFnP/sZ3vWud5Vc7nkerr32Wuzfvx+NjY2YOXMmbr755pLrfepTn8LWrVuhtcbFF1+MVatWRVnUwfzoRz/Chz70IWQyGZx00kn44Q9/WPX7V111FT70oQ+hqakJjz76aMX7/fznP4+Pf/zjWLlyJbTWWLRoEe66666ajolqIwbbEyeEeCuAy7XW7w/+/S4A52mtP1Lh+tcCOE1r/f6h3jZ0zjnn6LVr1w790RCNM0/sfg5P738BjYkUGhIpnLtgGRZ1HHv7ciIiIqLQpk2bcPrpp9f7MIjKKvf6FEKs01qfU+76tWRQRZnvlY1qhRCvBPB3AF42jNt+AMAHAGDBggU1HBbR+Ke1gtYKgmNmiIiIiIgGVUsX370A5sf+PQ/A/uIrCSFWAvg+gDdprY8O5bYAoLW+RWt9jtb6nJkzZ9Zy7ETjntIaWpsmSUCF1RkiIiIiIgJQW4D6JIAlQojFQogUgLcD+G38CkKIBQB+BeBdWusXhnJbosks3IMadfFlBpWIiIiIqKJBS3y11r4Q4iMA/gAzKuZWrfVzQogPBZffDOALAKYD+K4w3Ur9IBta9raj9FiIxh2tFQANSwhIzSZJRERERETV1DQHVWt9D4B7ir53c+zr9wN4f623JTpe5DOoAlIxg0pEREREVE0tJb5ENEwqGC0jwhJfZlCJiIiIiCpigEo0SlSsg6/p4gswgUpEREREVBkDVKJREnbwFRDBvCUNpVWdj4qIiIiIaPyqaQ8qEQ1dOPc0nkElIiIiGk0PbF83Kvd70clnD3qd1tZWDAwMAADuuecefOxjH8Of/vQnLFiwYNDrU6H3ve99uOuuuzBr1ixs3Lix5tv19PTgpz/9KT784Q+Xvfy6665Da2srrr322or3Uct1RhMDVKJRorQK9p+G+VM2SSIiIqLRt/HAthG9v+VzThnS9f/0pz/hmmuuwX333VcxOB2vwgSDZVll/13r7ap54IEHcNttt+G2226reJ2rrroKH/nIR/Dud797SMff09OD7373uxUD1ImAJb5EoyTs4CsQZFDZJImIiIjGyPI5p4zIf0P10EMP4eqrr8bdd9+Nk08+GQDw5je/GWeffTaWLVuGW265peQ2O3fuxGmnnYb3v//9WL58Od75znfi/vvvxwUXXIAlS5bgiSeeiK5b7r527tyJ008/HVdffTWWLVuGyy67DNlstuTn/Pd//zfOPfdcrF69Gh/84AchpSy4/Yc//GGcddZZeOihhwr+vWfPHnz961/H8uXLsXz5cnzjG98oe7s9e/YM+fmq5MILL0RHR0fV66TTabzuda/DqlWrsHz5cvz85z/HZz/7WWzfvh2rV6/Gpz71KQDADTfcgKVLl+KSSy7Bli1byt5XteuUe94+85nP4Lvf/W50neuuuw7/9m//doyP2mCASjRKopU0EexBZZMkIiIimsQcx8Gb3vQm/PrXv8Zpp50Wff/WW2/FunXrsHbtWnzrW9/C0aNHS267bds2fOxjH8MzzzyDzZs346c//Skefvhh3HjjjfjSl7406H1t3boV//AP/4DnnnsOU6dOxS9/+cuC+9+0aRN+/vOf45FHHsGGDRtg2zZ+8pOfRJdv2bIF7373u7F+/XosXLiw4N9HjhzBD3/4Qzz++ON47LHH8L3vfQ/r168ve7vXvva12L9/f9nn57zzzsPq1avx/ve/H7/97W+xevVqrF69Gn/4wx+G9Xzfe++9mDt3Lp5++mls3LgRl19+Ob785S/j5JNPxoYNG/C1r30N69atw89+9jOsX78ev/rVr/Dkk0+W3E+161R63t7+9rfj5z//eXS922+/HW9729uG9TiKscSXaJQUlvgKKGgosEkSERERTU7JZBIvfelL8YMf/ADf/OY3o+9/61vfwp133gkA2LNnD7Zu3Yrp06cX3Hbx4sVYsWIFAGDZsmW4+OKLIYTAihUrsHPnzqr3dcIJJ2Dx4sVYvXo1AODss88uuA1gyo7XrVuHNWvWAACy2SxmzZoVXb5w4UKcf/75Zf/98MMP4y1veQtaWloAAFdccQUeeughvPGNbyy53T333FPx+Xn88ccB1FbiW4sVK1bg2muvxWc+8xm8/vWvx8tf/nJ0d3cXXOehhx7CW97yFjQ3NwMA3vjGN5bcT7XrVHre3v3ud+Pw4cPYv38/Ojs7MW3atBEr52aASjRKVNgkCQKWEIAGWOFLREREk5VlWbj99ttxySWX4Etf+hI+97nP4YEHHsD999+PRx99FM3NzbjooouQy+VKbtvQ0FBwP+G/LcuC7/sAUPW+4re3bbukxFdrjfe85z3413/917LHHgaf5f5drYdI8e3G0qmnnop169bhnnvuwT/+4z/isssuK7tnNeyHUk2l61R73t761rfijjvuwMGDB/H2t7996A+gApb4Eo2SfBff6Dvcg0pERESTWnNzM+666y785Cc/wQ9+8AP09vZi2rRpaG5uxubNm/HYY48N+76P5b4uvvhi3HHHHTh8+DAAoKurC7t27arpthdeeCF+/etfI5PJIJ1O484778TLX/7yYT0GALjooouOOXsKAPv370dzczP+1//6X7j22mvx1FNPoa2tDf39/QXHfueddyKbzaK/vx+/+93vSu6n2nWqPW9vf/vb8bOf/Qx33HEH3vrWtx7z4wkxg0o0SqRWUAiaJEGYBCo3oRIREdEYGOlOvkPR0dGBe++9FxdeeCG+8Y1vwPd9rFy5EkuXLi0ohx2qyy+/HDfffPOw7uuMM87A//2//xeXXXYZlFJIJpO46aabsHDhwkFve9ZZZ+Gqq67CueeeCwB4//vfjzPPPLOkjBgAXvva1+L73/8+5s6dW3LZeeedB8dxSr7/la98Ba9+9asLvveOd7wDDzzwAI4cOYJ58+bhi1/8Iv7u7/6u4DrPPvssPvWpT8GyLCSTSfzHf/wHpk+fjgsuuADLly/Ha17zGnzta1/DlVdeidWrV2PhwoVlA+uzzjqr4nWqPW/Lli1Df38/TjzxRMyZM2fQ57FWYjyeMJ9zzjl67dq19T4MomNyNN2Dv+58Bl2ZPsxonYpD/V0488SlOPPEpfU+NCIiIppENm3ahNNPPx1AfeegEpUTf32GhBDrtNbnlLs+M6hEoyTagypMBhVaQWs2SSIiIqLRw0CSJjruQSUaJUorMwdVBHNQOWaGiIiIiKgqBqhEo0Rp0xQpnIOq2SSJiIiIiKgqBqhEo0QqBaWUKe8NmiQpplCJiIhoFIzHvjJEw3ldMkAlGiUaKp9BFcygEhER0ehobGzE0aNHGaTSuKK1xtGjR9HY2Dik27FJEtEoCUt8802SuAmViIiIRt68efOwd+9edHZ21vtQiAo0NjZi3rx5Q7oNA1SiUaKUglIawrIAATMHtd4HRURERJNOMpnE4sWL630YRCOCJb5Eo0TqoMQXCDKo3B9CRERERFQNA1SiUaKjOagWBEzJL5skERERERFVxgCVaJSEAWk4B5VFvkRERERE1TFAJRolSitobbr4AgIAS3yJiIiIiKphgEo0SpRWUFBBBpX5UyIiIiKiwTBAJRolUitT4guTQVVaQWlV78MiIiIiIhq3GKASjRIdzD21hAjKfPONk4iIiIiIqBQDVKJRIpWKmiQBgBCCnXyJiIiIiKpggEo0SsJsqSXMn5klLGitWeZLRERERFQBA1SiUSK1gkK4B9X08dVgiS8RERERUSUMUIlGidYKWqto/6kQAlqDJb5ERERERBUwQCUaJVIraI2iPajs5EtEREREVAkDVKJREu43jTKoENDgHlQiIiIiokoYoBKNknJdfDW7+BIRERERVcQAlWgUpN0slGmJFDVJsoIAlU2SiIiIiIjKS9T7AIgmG6kU1u5+Hr7yAcT2oLLEl4iIiIioKgaoRCOsc6ALfU4aaTdb8H3TJIklvkRERERElTBAJRphh9Pd6M72Ie2UBqhh4yStNXwlkbT5J0hEREREFOLZMdEIczwXru9hestUtDY0R9+3kM+gPntgG7qyfThvwXI0JRvqeLREREREROMHmyQRjTBXevCkj46WdjSnGqPvm72oGlordGX74EsfXZne+h0oEREREdE4wwCVaARJpeD4HhQ0EpZdcFnxHlRPeizxJSIiIiKKYYBKNIIc34UnfSSs0sAz3IPqKR9KKXhKwRL8EyQiIiIiCvHsmGgEudKDVBJJ2y65zArGzOQ8E8RqrThyhoiIiIgohgEq0QhyfA+u9JGskEFVWiPnO/CVhNaA5sgZIiIiIqIIA1SiEeRKF77ykSizt1TAlPhmPcdkUMGZqEREREREcQxQiUaQJyWkUiUNkoBgDyo0cr4JYlniS0RERERUiAEq0QiSSkFpHYyUKWQJgTBh6rHEl4iIiIioBANUohGkoaChYJUJUM0eVJMxVUqxxJeIiIiIqAgDVKIRpLSG1hoCZQLUYA8qYDKnZiYqS3yJiIiIiEIMUIlGkNYaWqNsiW+4BxUAlFbBdZlBJSIiIiIKMUAlGkFmD6qqHKDqMEDVLPElIiIiIirCAJVoBCkoKJQv8bWEgAoyqBom08oAlYiIiIgojwEq0QjSpjVv+SZJEEC0B9VkWrkHlYiIiIgojwEq0QhSWkOh8h7UMByVwf5TBqhERERERHkMUIlGkFIK0KpCia8FrUxAqsP/scSXiIiIiCjCAJVoBJmy3fIlvpYQkEEOVSsdjZohIiIiIiKDASrRCFLQpklS2QDVMhlWBIEsNBRY4ktEREREFGKASjSCwtmmFQPU2JgZcA4qEREREVGBmgJUIcTlQogtQohtQojPlrn8NCHEo0IIRwhxbdFlO4UQzwohNggh1o7UgRONR0oraK1hldmDaltWcLkyM1DBMTNERERERHGJwa4ghLAB3ATgUgB7ATwphPit1vr52NW6AHwUwJsr3M0rtdZHjvFYica9ahlUwHTylUGZL4JglYiIiIiIjFoyqOcC2Ka1flFr7QL4GYA3xa+gtT6stX4SgDcKx0g0YUhlmiRVClABAV9JAMFIGmZQiYiIiIgitQSoJwLYE/v33uB7tdIA7hNCrBNCfGAoB0c00ahgfEy5MTOA6eQbBajQkMygEhERERFFBi3xBcqeaQ8l7XOB1nq/EGIWgD8KITZrrR8s+SEmeP0AACxYsGAId080PoT7S4UQVTKogC9NgKrZJImIiIiIqEAtGdS9AObH/j0PwP5af4DWen/w/4cB3AlTMlzuerdorc/RWp8zc+bMWu+eaNxQWkNrVMyeAma1x1c+AARzUJlBJSIiIiIK1RKgPglgiRBisRAiBeDtAH5by50LIVqEEG3h1wAuA7BxuAdLNJ4N1iAJABBrksQMKhERERFRoUFLfLXWvhDiIwD+AMAGcKvW+jkhxIeCy28WQpwAYC2AKQCUEOLjAM4AMAPAncEJewLAT7XW947KIyGqMxWMj6kWoBZkUMExM0REREREcbXsQYXW+h4A9xR97+bY1wdhSn+L9QFYdSwHSDRRSKUglape4isEvKiLr2KJLxERERFRTC0lvkRUAx30DrOqZlAFZNAkCWCZLxERERFRHANUohGitIYarMQ3NmZGCMFZqHTM9nRl0Nnv1PswiIiIiEYEA1SiEaK1AnT1Et+klYgCVEtY0FpDKlnx+kTVPLS1Exd+7c946Zf/hB1H0vU+HCIiIqJjxgCVaIRIpaB09RLfOe0z0NrQjMXTT4QlLEitsHbv8zg80DWGR0qTxbt+8AS0Bjyp8Y+/eqbeh0NERER0zBigEo0QpfWgXXxTdhILO+agJdUE27KgtELOc/H8oR1jeKQ0GR1mmS8RERFNAgxQiUaIhtlPWnUOaowlBJRS8KQ/ykdGx4NqmXsiIiKiiYIBKtEI8aQPpRSsKntQ48ISX08xQKVjZzE+JSIiokmgpjmoRDS4A32d6MsNoKWhqabr28KU+CrFLr507JhBJSIiosmAGVSiEZD1HHRl+pD2cpjWPKWm21iWBaU1S3xpRNhMoRIREdEkwACVaAT4SsJTEkk7AUvU9mdlCSvYg+qN8tHR8YAZVCIiIpoMGKASjQClFLRSQwoSoj2oUkJrBaXVKB4hTXYWM6hEREQ0CTBAJRoBUisoaIgaGyQBgC2E2YMa7EOVigEqDR/jUyIiIpoMGKASjQATaOqay3uBcA+qMsGt1vCVHMUjpMmOJb5EREQ0GTBAJRoBJgs69BJfkzmVkFpCMkClY2AzQCUiIqJJgAEq0QhQSgHQEMPYgyqVCW5Z4kvHwuK7OREREU0CPKUhGgEy2Es6pBJfISCVhIaG1IolvnRMOGaGiIiIJgMGqEQjINyDOpQMqkZ+BqrZi8oAlYaPe1CJiIhoMmCASjQCpAqbJNUeJKTsJDwVBqjs4kvHZiiLI0RERETjFQNUohGgtIbWGmIIJb4NiRQWTJuD1oZmKKXgB8HqWOvK9GHH0X3QWtfl59PIsBmfEhER0SSQqPcBEE0GKpiDmhxiFmtKYwuyXi5qllQPzxzYCqUUmlNNmN3WUZdjoKFTigsKRERENPkwg0o0AsJOvMPZByggoIMMbL1kPQd9uXTdfj6Vt+toGv/w06fwzfu3lrw+XFm4oCEZrxIREdEkwAwq0QhQWkFrPaQuviEhggB1FI6rVlkvh5zv1PEIqJyP/WwDNuzpwd04gNULpuIVp86MLnP8wgDVl9zDTERERBMfM6hEI8CU+KphNaoRQkBBQ+n6BRgZL4ecxwB1vNmwpyf6+t6NBwsuc4sDVJb8EhER0STAAJVoBMhwzAyKAlStccKmDWjft6vibQUEUO8SX9dBlgHqhOIVl/gyQCUiIqJJgAEq0QhQKizxLQxQm3q7MHXfLszZtKHibYUQUFpD1SFA1VoDWsNTPqSWdc3i0mCK9qCyxJeIiIgmIQaoRCPA7EFVJXtQhZT5r5Usvpn5PkygWI/gMMz8AkAQq9I4Vfy7KW6SxBLfiUlphReP7kPazdb7UIiIiMYFBqhEI0AqE+gVZ1Bt34u+TuTKn4AOZ9/qSFFKFQTG9W3VRNUUB6i/3bC/4N/DKfGt18II5e3v7cSLR/fiyT3P1/tQiIiIxgUGqEQjQEFDQZcEm7bnRl8ns5mytzVNktQ4yKDWdx8sVRdfPOjsd/CdP28ruLx4T2ot1u3dhMd3bWSQWke+kujLpaGUgif9eh8OERFR3TFAJRoBSiloVTpmxnZjAWqlDCpMdqwee1DD8Tg0sazb1VXyvaFmUJVW6HfSyLg5BkZ15iuJATeLrkxvvQ+FiIio7higEo0ApU0GtLjENxHPoOYqZ1Drlb2UsRJfDWZQx7P4r2ZGa0PJ5UPdg+r4HjwpobTm3uM68qQPqSSybg4DDvehEhERJep9AESTQbgHtbTENz+6pWKJr8mh1mX/p4qV+ALcgzqexX8z5WJRXw41QHXhSR8Jy2aJbx150oevJAAJx3cHvT4REdFkxwwq0TEKs6caKC3xjWVQrQpllGYPan1KfAsyqOziO64UZ7Pjr49y5bxDz6C6UWkvFybqx1Mmg+pJHzmfs4iJiIgYoBINkyd9bO3cg/5cBlKVlvcChXtQLVU+SyUggGBMzViLzz7VdcriUnnFY2Q8WT1AlRVeX5XkfBee8kyDL65M1E2YQXWlh5zvQmmFnV370ZdL1/vQiIiI6oIBKtEwvXh0H/b0HMT6/VugoWFZpX9O8QyqqBBAWEJA6foECUrlmySxi+/44vqFr5ecl5+j65d5LQ01gxo2R9JKQQ0xuKWR40kfUiv4ypT47u/txI6ufXhq3+Z6HxoREVFdcA8q0TA5vgvHd9GUaqycQa0hQAUENOpU4qs5B3W8cooCVMdXuO+5g8h6Ek1Ju+T6Q9mD2jnQjQN9R5DzPWhwFmo9+UpCKoWEZcP1fXRn++H6PhqSqXofGhERUV0wQCUapqSdQC4IUBVKR8xAa1gyn/USSqIcIepXXhtvksQuvuNLcYD64AudePCFTgDAq5fNLrn+UMbMdGX6cKDvCDJuFkpPZYlvnchg9qmGRkOiAZ7ykfMcONJjgEpERMctlvgSDVPCsuH4LrQ2JZLFGdTipkiVMqj1HzMTBqhg/nQcKS7xjfvDc4dKvleu7LcSR7pB59jw987ffD140ofSCrZlw7IsKKUgtYLLbr5ERHQcY4BKNExKa0il4Pp+MAO18M+pJECtUEYpYALUepRZqnhgzD2o44rjl8+4V6I08I5bHsOj248Oel3P9+FLH0k7aRZYWOJbF1JL+ErCFhYsYQXvKRKelPy9EBHRcYsBKtEwKW0aDHkqyIIUB6hBgKGD5knjPYPKHOr4Ui2DWsmjLx7FO7732KDXCzOoKTsRjBfi770epDKBqCWsoFmagqckZLAv1aswmoqIiGgyY4BKNEy+kkE5ngelNURRia8ITi5lMgkAsCrtQYW5XV0CVC2hdBBIcw7quFK8B3Wk9DsZuL4HT/lI2omgSRJ/8fXgKwWpNSwhYAkreg/wtQlQ/QrvGURERJMZA1SiYQqzH76SZg+qVb7EVwbNTqplUOs1ZkYGQTbAvYjjjeONfICa81ys3fOcKSu1bFNWqtSQZ6jSyAiblFmWyaCGf4sqyKIyg0pERMcjdvElGiYV7BHzlQ9hJ0pLfIMOvoMGqDCBoapDcBgG1wb3oI4nrhz57FnOd5Dz3CgQEkIE/aMZoNaDDBe3hAUhLOjgb9HXyvzHDCoRER2HmEElGqawPM+XEkppiApNkgoC1DIBoCkNFnVpiuJLU0poWzZ3oI4zo5FBVVpDaoWeTD+kkqZBF0t868ZXpsTelPiK6PcgJTOoRER0/GKASjRMUskggypNmV7xmBnfnFyqRALaCi6rEAiYRkljvwfUVz6klrAtq26Nmqi80diDGpaU9uYG0N7UFnvd8fdeD+HvI9/F1yxiSa0glYSvGKASEdHxhwEq0TCpYP6p6eIrK46ZUXYCWtjmexVK9ixRn1EzftAt1BZ2yR5UT/rcm1hHw+niOxipVLRfeu6UGVEHaWZQ6yPsoh128dXB6KrwMm8UyryJiIjGOwaoRMMUZk59aRoNlWRQg5NLZScGHTUDmOBwLDNZWmsThGqFhGUXXOZJH4/s2ID1+zaP2fFQoaHOQY2r9DpSWkFDY0pjS9AkSUChPjN4Kd8JPCzxlbF9p77y4fhunY+QiIho7LFJEtEwhA2SIEww4JfJdOQzqHZNs1CBse2iG2ZPTYOWwj2wXZleOL4HiOyYHQ8VOpYSX6k0ErYo833TlCd8vYk67X0mQypl5qBayWDMjCntBQBPSrjSq/MREhERjT1mUImGwZRK6qis1/G9knLYeImvGixAxdiPmgnLC23LMp2EY3tgB5wssp4zZsdCpY4lQPVV+deR1AoKClbw1s8S3/oy2wR0tEiktIavFZJ2Ap7yzSIRERHRcYYBKtEwhMGdEALTmqcAAmhvbCm4jihb4lt9D+pYlvjmGyTZQFSebH5+2s0i6+XG7FioVDxA/djFS/DHT1xY8209GczTLMqMqnBhJXg9WmySVFfxEl87aJKklERjsgG+9OGyxJdo0vGkz/dcokEwQCUaBqlNB19bWDixfRaWzlqEhF1YMV/QJKmGEl89xnsB8yW+AlGBsWaAOh48u7cX3/rT1ujf7U1JJO3a3659qfHsgW14fNfGgsy+rxQU8h2nBQQUWOJbL0oHJb5hBhUavpJosJNQ0HClz1moRJNIxs3hkZ1P45kDWwe/MtFxjAEq0TDIaH5hPhNVLD9mxoa2wi6+VZokjXGpZZi9sYUdBMj5OaiO9FheWCd9OQ/v/P5jBd+bO7UJyUTtb9eO76NzoBt9uXTBQkPYeToKUIUp62aJb32Eo6qscMyMUtFc4qSdgCd9uPw7JJo0jqR7oLVCd7a/3odCNK4xQCUaBsf34ElZ0v02Luziq2vJoKIOJb7Sh1JmBiqA6Od70ocMOhPT2Fu7swt9ucL5l3OnNiJplS6CVNKTTSPnOVBawlcSnQPdQddpBa11bGGF82/ryVcKsmjMjK9M2X3SSrCTL9Eko6GhKvQIIKI8dvElqiDtZrG35zAWdcxBQyJVcFnOd+BJH8lE5T8hK+jAKeMBqq6yBxVj18XXVxI7uvZjwMkimUgGnUM1NEyAGpUVBsGLKJMhptFxsLe0OdXcqU2wh/A76M4MIOPl0JBIYWvnbqTdLGa0TAOAIGMX6+ILzcWIOgm7gVuWgBAWZNDF17YsJOwEO/kSTTJam/dbG5UXt4mIGVSisrTWeHLP89jZtR/7eztLLs95LlzpI2UnK96HHZX4JqFFrXtQxyZA7c+l0ZXpQ8bPYUZLezAux/znSi8adaGD/9HYebFzoOR701tSFUt8L1o6s+R7/U4OWc+B0gppLwdX+jiS6Yn2TocZVBE152KAWg/h2J8wgwqY5mW2sJCwbPjKZ4BKNImYrTx8vyUaDANUojKOpHuQcbLoc0qDBQDI+S5c6SFlV8mgBnvHVCIBZZvV0moBqlQS3hidjEqtILVCg52CbdkI2yQBGq70ogwq9yeOve1lAlQhBJJl5poCwLK5DSXfc33TACtskORJDwKF3afD+zVZPP6O6yH8fYQLBgDgSh9CiCBAlXB9v8o9ENFEogEuCBLVgAEqURldmT705gagNcqWt+Y8JwhQK2RQtc538U0Mvge1JdWEASeDzoGeETn+wZg5rioaNyKAKIPr+j58ZY79eNufuLVzD/b1Hq7rMbx4JF32+0mr/Nt12uvDF9+4rOB7rjTdesOVelf6SNqJqKTUDjOoMKXlDFDHXphJ0bGuyoApv29ImIUjnyW+RJOKKfHl+y3RYBigEpXRne1Dv5up2Fk357vwg5P+coRSEEpDWxa0ZQ9a4tve2Iq+XBpHMz0FY0FGS757aHhiLKJyXk968MfgGMab3uwA9vQcxNYje+p6HAd7C8f7fOKSUwEAliWQKNMoSQjgPS9dhOUnTom+50kFHcugur6HhJUwv3fEM6hmNZ8r+mNP6jCbnf8YPm32YiyZuQAJy44yqJ5kBpVosjBNkvh+SzSYmgJUIcTlQogtQohtQojPlrn8NCHEo0IIRwhx7VBuSzTeZD0HA04Gru8VZKHilzu+CwgBu0IX33h5L4Aog2pVmGmYtBOwLAuO741JxqS4m6uI9qBqeCqWQR3j2az1lPMdOHXOViml4fj55/trb12JD77ipOjf5Wah2kHQmohlWD0pC167XrCYIqMxM/kuvkqzSVI9KKWKFomAhGVHDdm4B5VocunK9GFv72FWrBDVYNAAVQhhA7gJwGsAnAHgHUKIM4qu1gXgowBuHMZticYVT/r5rEXQOCiu30kj4zloSpbu/QuF5b0yYUqAwzmolTKowNiO/AhnoMYzqCHX9+HL/B7U4+Wz1PE9OF59R3rEg9OGhIW3nTMfjcn8Iki5fahhXBrPrnrSBD9hKbevJOxgzqZZmDDXDUebcEV/7EmtoHX5GcoAkLBtSKUYoBJNEs8c2AqtFVSFbv5ElFdLBvVcANu01i9qrV0APwPwpvgVtNaHtdZPAij+JB30tkTjTRi8AYA2eaiCy/tyaWTdHJqTjRXvww4zqHZhBlVUyKAC8U6+Y1HiW5xBzc9h9ZUfe/zHTxffscpeV5Pz8q+PeGAaKptBDeKbhB3fx6iicQae9KGCUTLhfyL6vVvR92hshXtQ4w2S4hJWAp7y4fn+cbUPnGgy86RkBpWoBrUEqCcCiG/K2ht8rxY131YI8QEhxFohxNrOztKxHkRjJRz9AKBkD6rWGr1ZM2OyOVUaoPZv3ITMzt2w/HyDJCAfqFqySoAKEayujl6w4PoKf958GF1pt+zJcdgwJzwhPp6aJDm+a0q36yhbEKCWvj2XC1DDDFz8Ms+PBajKB4L5mkorCCEKMqiAiJon0diRWhXsBy5mBVsIfCXzc4mJaEIKP0d96Y9Jnwmiia6WALXcp2etZ6w131ZrfYvW+hyt9TkzZ5bO9SMaK+GJPJDflwmYAOaZA1txeOAoHN9FUyyDKtMZbP7MF/HUm9+FZ997DZAzjW7CEt8wULWqjIywhIAa5bEun7vzWbz3tifxkZ9sg+PLfKCCIFuqdUlQevxkUF24vgfUMSgfNIOaqL3E1+w3lUg7WSitTSZV6ZJFCUsIKKV50jTGlDKNrCqV+AKAbVlm1AzLfIkmtHD/f7gwRUTV1RKg7gUwP/bveQD213j/x3Jborrwg+6ntmVHQRsAHOrvwo6j+7Gz6wDmts+EHWtKs+d7P8ahX92FGZe9Erk9+3DwvgcAlMugVg5QwxLf0QwU7li3FwBwqM/DtkM6GjMDYcaNhCXG5gNUFDz+yc7MtvWhKnRuHpNj8PK/+6YaS3wtYX5n8dejp8zxS60w4GSgYUrX4zNQo9tb1nHVDGu8iDKoZddxDUtYQbOr4+NvkGiy8qUM5h4r7vknqkEtAeqTAJYIIRYLIVIA3g7gtzXe/7HclmjUdWf6sLencO6l1BIKCgnLLijxlUrC8V1MaWrFlMbW6Ppaaxz6zT2Y+tI1OOOmr6Jp4XzsvffPAAAVzElVtgk2BgtQlR67PZ/9OR2bh4moIZQK9p1GDXSOk5PjMHMe7g2sh5yfz6A2lAlQU2UDVJN1jzdQ8mVYTiaR9R3oYJ9pfAZq/vYCMjaSRmmFLYd34Wi6ZyQeElWggjEzlfagAqbsHzyhJZrwTG8HGSyA8u+ZaDCDBqhaax/ARwD8AcAmALdrrZ8TQnxICPEhABBCnCCE2AvgkwD+WQixVwgxpdJtR+vBEA3V0we2YtuR3eh3MtH3TOdTDduyoqwikM94hGMgQgMbNyG3Zx9mv+m1EEJg1mUX4chTzyI3kMlnUINS36olvsEe1LEqtcy4iGXTBBA+2qDE1ZQeatRe0T9xKa0gtYyaQtWtxNeNlfgmatuDKmAWSRKxy6QyCyyLps/Fwo45USfmcA9qnCUKM6gH+o5gX+9hPHtw+wg8Iqok7LBcrcTXChateEJLNLH5SkZ/8zpoj3+8VCcRDUeilitpre8BcE/R926OfX0Qpny3ptsSjSdSqfxYGeQzabawC/ZjmuyaKinJ63niKQDAtJedD2iN5YtmYJfS2Pn0C5ix8kxz21pLfLWGHqOT0YwTy6AGWbjwZFhrU/57vIyZCRclgCCLXK8ANZZBbUqVK/EttwfV/M6SBXtQNYSw0JJqCkp7w+yoLsmgCgizNypYGMm4Djzpo8EqXIihkWV+J5WbJAH5qorjpYqBaLIKpwMoqKhSSg9S4k90PKulxJdoUivukBmudNpFe/PCIKY449H31DNonH8iGmbNQFPPUZzY0YK26VOxY/0muM2mFDhe4mv5Huav/yumHNxbcD9jfTKadXVJBlUXZFCPn72J8dFC9exoG9+D2pgoDVATZTKoCPYtx8fMyNjrVEBEOfDyGVQBBY2NB7cj4+bgK59NecZA+DobrMQ3XsVBRBNTOB1AqfBztn4LoUQTAQNUOu4VD80OM04Jyy4ocNU63JuZ/7PRWqPvqacx5cyVAIDG/l4IIXDiy9Zgz+ad6GpsMz8j1sV3xo4taDnaibkb1xX8XEtYo7r/UarCD8O0Iwr2oIYdi83qrglcJkKBb7+TwcG+I8d0H/HOzfWUdauPmam0B1VDFzRJ8lV+8cEsfOSD75I9qJYFpTUc38VzB7eb2ZsMUEdduAe1WgbV7APnCCCiic6TfvA5Y6qkjqcRbkTDwQCVjlvhPhA/3BMSkEE2zbJsICjrBYI9qEUnlOlNL8DtPIqp550NAGgc6AUAzLzkQmjfR9fDjwEoLPFt6O8tezwi6Jo7Wquqrl94kjuQQ9TFN/6Y4pmdsSw5Hq51ezfh+UM7cDRd/nmtRbg3CEBds8bDKfEVFZokFc86RbD4UG4PqgrK3HO+C19KeFXm9dLIMB09Sysy4kzZP9gkiWiCi0p8g0ZJRFQdA1Q6boUBZ3EJXRisJCy7oOQ23IMaP6E8fPcfAdvGjEsvAgA09PcBAJrPPRvJjmk4+j8PmdtGAapEKptvyBQnRrkhSkmA6oiC/S9hYGaCdRGMvRn/GVQASLtZdGV60Z3pw7o9m5B2s0O6fXw2XT07F8dLfBvKlPhWHDOjFBJFGdR4pj96banSklIrGG/kKR+2ZcFjie+YUEEGRVQr8Q2y3zyhJZrYwgA1/Kw5XrbPEA0XA1Q6bqnYTLJ451xfS0iofBffaMxMYQZVuR4O//b3mPaSNUh2TAW0RkO6HwDgtk9Dxytfhq6//BVaKWjLghYCQikkqwSooxkcOUVZsYwjCspANXQsSxyOuJgYZUgDbhb9TgZPH9iK3twAthzeNaTbh/uDANS19CrnxUt8ywSoZTr7imAOakEGVRVmSqORQSgNUIUQUQbVtuwgg8oAdbSF84arZlBxfI16IpqsfCWhohJffdw0ICQaLgaodNxS4YdEsJJ5NN2LjQe2I+s5JiMlbHMZ8hnUeFOTQ7++G86BQzjxve8AAFi+B6EUVCIBlUii/axV8Hv7kNu7HxAiapQU/Xy7sIl22KxmtFZVPamL/i2i74VzUMMW+JawIABMlA6iA04GA8GoIE/6Qw4w43tQ61ri6w19DyqCsnDbKm6SFMugInhcZZp8WbCgYALUhLDhKx9OlXFINDKkKq3IKBYuHGkw00I0kflSRovcYT8LNj8jqowBKh23woBTa4W+XBob9m3Bru4DwWUatlU4ZkYWZTwO3Xk3Wpaego4LXwogP0ImDDxbTl8CAEhv3mq+H8xCDVnKL1hCFdE+wbEp8QWAv7/tEP7lV0eQdU0pr9IqaH0Ps7kRwHgv8hUAHN9FzncBICpVHQo/lkWvZ1AeD1CbymRQy2VVwyCmcA5qYSAalfhCR/uOQ5YQUErDk57JoiszE5ZGl6ne0FW7+Ibl1xNhkYiIKpNaBn/zMjqvmAjVSUT1wgCVJry0m8XGA9uHve9QaY2uTC96sv3IerkoSLQtC9D5Et/wA0UIAZnJom/Ds+h4xQVRKaUVZJ1k0LG35dSTActC1zNb8MCmDBwUBRcaELHSYmuU95uVC1B9Bew66uPuDQ40woZRJqARwUGO5w/R+EiYjJsDAPhBqepQSC2hEGZQ6zfWo2DMTJlgtFzQaglVMgfVl4UlvlH5uCqTsQuCV09J5DwHju8AALvHjjIVzESsOgcVZvGATZKIJrawSkfFFpyYQSWqjAEqTXjPHtiGwwNd2Hhw+5Bup5SCDkpufCWjAdoyaCRTXOKan4NqoffJ9dCej6kvXRPdX5hB1UEG1W5sRPPiBdjy6HO47eE+7Ogu/TAKbwPkO3aOVkBYLkANrd/lmxLfICgRQhTMZZXj9AQ5/J0AiBYoPOUjMcQAVcXup56BWXaQEt/mMp19BYImSQUZVMBCfA+qFc24Lc7Yaa3gSg9aa/haIed7wfc5p280Rfu9MXiJL38PRBObpyR8rSBl2CJJI+e56M701fvQaBLz5MTdrsMAlSa8nO/Ckz4czx3S7aJuejpoDqTyTYIsywoyG/kxK/nyV4HuR5+ESCbRfvbq6P7sogwqADQvORlqzx4AQL+0Sk40rdhevzCDOlrBoFtldEh/zuQNw58tEHb41djVfQCP7NiAvtzAqBzXsQh/JwCQCbLfvpRVyybL8VU+c11L8wpfjU4J7GBNksqNnkEwZiYR34Na1B0232ynNIOqtI4CVHMM5u8orBjYcngXNh3acUyPi0rl93vXMGaGASrRhBY24gu3T2gAmw/vxNo9m/D0/hfqe3A0KT1/8EU8svPpqD/HRMMAlSaF4ew7DEeqRONFgkyU0gq2sErGrMioSZJAz1+fwJQzV8BuaozuTxTtQQUAnDAXbb0HAa3QrwqbIgGlGVQFHZWajjSnSgYVABTynUWFaeMLrQFHehhwMth0eOeoHNexkMHe0aSdgOO7JhM+jAyo2R8UBofVZ78eTffgkR0bov3KI2k4Jb4iyLAliuag2gUlvogFqEVdfGHKosPnLCzxVVrDkz729R7Gwf4jLPcdYfmxVYPtQVVskkQ0wYUNkk5om26+oRU85WNn9350ZXrHbZUSTVyH091QSuFQf1e9D2VYGKDSpOBJf8hZs3iTJCB/Aq90mIET0XXC6wkh4Pf0YmDTC5j20nML7i/MoKpYBjUz7QTY0kdzfxe6VGGTJKAoQB3lsS7FXXyL5TwThGulogxqmJ3syfUj6zmjclzHIsyghntO02426pI4FDKYUWcXzb4tprXGswe3ozvTh709h475+Is5/tAzqJZlurzGS3x9VdgMSUBEe5+K9zzOaJlqFieC37UTjJhRWuHFo/uCrsgciTDSwpK/agtrYeabJ69EE5fSCr7yobTGjNZpaE41Ru+nfvj+yv2oNAxKKzx/8MWKQajSCgl7aFuexgsGqDQpmAC1cqlcOWGJXRjMqGCIttQatmVF96dRuP+057G1gNYF+0+B0i6+ANDVNhsA0NZ7EF0yVXKSb8XKbsM9n6NW4jtIBrWrPz9mxRKiYG9c2s3Bl35U/jlemN+LCahty0bGzQ1rbmT4+7Utq+rt+50MHM9Fby6NtoaWkXgIBbJuLEAtM/O03B7UsDQ7WTBmBoVjZoImSZ4s3Z+bsBNYMnN+/u9Aqeg6nemuqPyXGdSR5UsfUsqqDb3C94Tx3KiMiKqLf74AwcITAATbi9jRl4brUH8XDvYfxabDZhuO1hovdO7Cgb4jAMx2pKH25BgvGKDSpOBJb8gZVBllR8MA1QQmSuU7a5oTewVfSbP/VJj9p3ZLM9pWLCu4v3A/aTxAPdQ4CwDQ1nMQXTJZskYaz6BawjrmDyodNHwqZ7AANe2Yxxxm2YTIr+pKJeFJH26QXRsv4qN/EpaNATc7rFmyYWlwwrKrzp1Mu1lkvRx0bO/rSOrL5Z/ftsbSjHvZMTPQ2Nl9ABD54ymeg+pJH47vwlM+GhKpkvuwgm6xgHlOE3YCChoZNwfXH1+/88kgXCyQwXaCSqLuyzx5JZqw/KBCp3ARPf9ZXc/Z2zSxOb5bcF7W72Swp/sQtnTuAmAWRxJW6fayiYAB6jHSWmN/b2c04oLqY/glvvmA0IzhkNEeVMM0KZHKDNkWEOj565NoP/csWMnCP/oogxor8T3aPANKWGjtOYSjMgmlTPAQ3cYvLPFVMCuqw/XcwRfx8I4NcPzSTGe1JkkAkHEBKSV0cCzhYweCvZ5BoD6ehL9DS1iY3TYdju8OK9vnx0p8q3VNHXCyyPruqGW6e7P5D5r25tIAtWwXX6EhpURvtjf6Xs5DQeDj+G7VRgmmoVK4OGOZFX6lMOBk4SqfJ1AjzA/eT2zLHnzMzCjuSyei0ReOmAmrJYqrpbiFgoZLaV2yiOxKD1LKaGRiYoj9WcaLiXnU48j2o3ux6dAObD7MLpf14Aed8cIM51AorQuCERU0TJJKRfv3rCCDEd6/OnQE2Z27Me0la0rur1yJb7+0kWmbHpT4moBDKsBrbCq4Tf5n5ffEDseRTA8838fhgdL9CINlUPtzCvv6Dkd7beOzMzU0pJLw1fhqWR6W+FqWhSmNLZg/9YRhZZx85UMGpTDVRv2k3QwczxlWI6ZaFASoTaUBarkmSRAKfU4adqzEd8sBgcP9+cfQ1tCCtJvDzNZpZX+uECKqKAjL2zU00l4OjufyBGqEedKHrwbvNm2J0d2XTkSjL/qcKlqMksGC72h9ntDkJ5UsyKCGryXHdyd87wIGqMdAaYW9vYdxJN2Dvgnaxnmi86Rv3vyHkXkMZ1+GzWFU2MUXhWV3YXCmtYL716cAAB2vuKDk/sqV+A7kFAamzERLXye6VL600m8w3X/LzUHNBVnA6Di1wv7ezppLLXO+A8f30JXpK8h4DhagAk3wfNOwQYhwyEw+cyaVgj9IFnashU2Swg/+VCI5rDJpX8qoFKZagGtKfF1ojPzoD8eXURdf2xJoKZMtLdckKePl4CsfHS2FpbtP7cy/Xk6cOgsnTp2FWa0dZX92+PyZoEnEVvglBtxMNLePRka8pLwa09kbE/5Eg+h45is/KPEN9qAGEwJ8BqV0jKRWcGLnhiZbr+FIb9xVvA0VA9RjcKDvCPpzaaTdLKaMQsMUGpyvJHwtoZUJLocimoMaltkEbeBVbP9eGDSaE0og99d1aJx/IppOWlhyf+VKfAdyCukpM9HSfwTdMv99L2UCVBEL+MLy0n4ngx1d+6Pv7+o6gOcPvYi/7noGWw7vGnSlNec72Nt7GBv2bSmYXznYmBnfT+T32iL/IRqeHEst4Y27DKos3DM8jDJpGc6mE4Adjvopc3vHd5H1nGAkzciveBdnT8uVfhZnUC1h9l9rDayc11pwmRtbz0hYNqY2tVUtJwXM8ykgot+9ikrQmMUbSdH+00FKr8JSaz73ROPTof6uQbd4+cE4tHDhO+zYL4/zPaieHF/nExORGwSiKniNha+1nO9O+NcUA9RjsLf3MDoHunjyVkcmg2oCBjnE1aJwdExBBlWbYMWKBTw6aGbgZ7Nw1j6D6a98WdkT/eIAVSqNjKuRbpuJlr4jiE95ySQaAABtnQcxda8JIi0hMKttOg73H0VPti+67r7ew9jf1wmtFXZ1H0BPdgBZz8ELnbvKjn4Jv9ebG8DRTH5f4mBjZtKOmScblfgCgM6XIY3HDKpZZFCwEC4oAForeNKv+cPPlPfmZ9+iQjlrxs3B8T0k7eSodLXtG6S8FyjNoLY3m723WmtYFvDFN+Ybd3nDODxPSgghYMGUm0ttZswCHIMwknwl4Q/SwRcw7wnDafpFRKPvSLoHzx/ajrV7nq96vfAcxYq6+CKqUAFQMG/9eNGd6cMjO5/G9iN7630oE5rn+9Ec8/B1pqHheM4x9TMZDxigDpPSChk3i4znsPytjgaCsR8yOJkeirD1e34Oqvl/r2D0S77jZu/j66AdFx0Xvazs/RWX+KYd85pIT5kJW/loSvfg+qOn4NbeeTjcaPYCNgz04YTNz6Cpx+wZbU01wVMSbhBcZdwccr6Lvlwah/q7or0Gzx7Yhn29h/H8wRejn6+DjYJhuUd3th9Syqhh0mAlvgNO/vGb8lUBDRWVIUk1fpok9eUGzMzTaPyPWTAwnZBNoP3IzqdrKo2U4ep20LBGB21pimW8HBzfRVOyIdqbO5LiGdQpQYDal0tjw74tsQZHhUH31GY7KAM1QUxjMta5dxiL02EGFUGJb9jYQ4OLcCMpXFir1sEXCKsY8tsQiGh80FrjSLoHju8N+vcZlvRHf++xLRXmzo6t98REtKv7AKSU2NM78vPEjydhBjU8PwuryrKeM+SkzXgzMXsPjwM5z40CGQ1M+JWKiepophf9rjl5D8sua+3mq4LsW3jeHe4p9GVhZ12NIEB98FGIxgZMPe+sMnemkHBMmU8YoIYB38CUmQCAlr5O3N+6FABwelE2M+Fkzf/bNnwpo/2mOd+NAswj6R60pJqgtULGy0EqhbSbje5DBh1tXd90cMt5DtJeDr25Acxq7Ri0i29/Nnj8yo/KZrUGlJJBE53x0STJkz6e2rsZEALz2mdBQSMZK8lWWgFBYytXemiyGga9P6VNwxqBymM9Mq4DR3poTDagP5ce8b/5vmz+uQ0zqM8d3B4tUqycswQbD24uuM3UZivIdJsAMpXIZ/Ydf+hBja9ktCgT/3DjqJORFe5JGyyDGm9URkTjx7MHt6Er3Yuc56IxWf0zJgwgrLCLLwAg/x6r9Mj3NBjvfGW2DNn2xJzROV6EDfd0sLUprCqTWiHnuWgOtpNNRMygDlPOd+FJD0k7YVa+jrM3l/Fg06Ed6M70IRMEd0oNbfSHGTGDqHwuzBCZVc3YHFSYVar0+o1oWr0cVkPph9GMnS8gmcvCb2iE22z2AqZz5n7TQYC6qjFfbntEFpZwWkHwaAVlpmGJqvlPor2xFa0NzQWlQLKoK6BSKirv2NG1D0oruLEAt/YMqg+pZexDVCFlJ6NuyfXmBxlmpUygbkqSCwegh1nRWlYQfSXhK7MfMAzKy2ULs0FH28ZEKsoojmRWsVwHX0d6cHwXOd9Fb24Ajl+412lKkwUhrGiGb8rOvx7c4QaoQZDuBc9d2C7r+CtCGz2elDXtQQ3n0x5vJ69E41nGzeFwfxf6nQyyfuk2m2JhEBGO+yju74DjsELFD2ar09B1Z/rw151P41B/FzwZjIELOkWHVWUAChIYExED1GFyfBee9JGyk0GQc3y9uYwHnQPd2Hx4J9qb25CwE1FJYq3CPagyWGAIf4ee8tGQMAGCaWagkMtm4Ly4G02nn1L2vhr7egAAh5Ysgw5WBMOALwxQ2wY6o+sfdgsD1ESsyULCtqM3b096phTQtmELy+yZjUpuZRSYAfkMatJOYGrzlGjlLHxpDhqg5kw22Q32ZIbBmqd8pBLJcbMHNdxn4Ukfnf3dyLpOtE8yzKDKYD9GLQsWxTMpFco3QHJ81zwXdiIKCkcyi1oYoJrHY0HACcq6LWGVLBA0p6xoIUFpVZBBHWzPcTl+kC1XWpk5ajDVaMfjCv9I86XCc/t7zUKallA1jJkxe931cVf+RzSedaa70ZsdwICbhVOmD0SxqKQ/VjERnnuIaDvF8fX+6gdBOw3d0we2oj+XwabDO6LXTTin3g+afQJmW9JExgB1mHKeA1f6aEikjss3l3oLy3mVVjixfZZpJqLVkDKoMvaHHJZInDJjAeZNnY3WhmYA+ZPz7i0vAL6P5tPKB6hWUJIbjo8BzFxRAHAbWqAamtDcezi67EiusMmS7eQ/5BKWHc22ilZehV2S3fO1QiyBmm/EICzMaJmKllRTQdDuyvxzc85JPqyiPk9KA65vw/PNwktY3pz1HLSmmsdNiW8YUHrKx5F0D2zbRlvw+wozyjIooayl67CvwhJfYboAB+XBxTyVP8kI5+OOdgbVtizkggx4mB2Pa0qJ6HUBAKnYpo3hlPhK5Rc0BgPyGdTjbYV/pL33tifxum89jI/+bH1Q7aBL5iIWi2fHiWh86M0OoN/NYMDJIOu5qP5XbD47fK2QEEGJb/CeHX6emPqU4+tv3A8WmWl4wr4UUudn6eYnDEjMmTKzIIExEU3so6+jnO/C9T2kEklwhXvsxRvbACa7NNTxIvFRIWFjocZkClOb2qLrhCfr3c+ZLn0tp51a9r5sz9xeJfOzKPuywbEIATljFlLd+QC13ynag+rGA9QEPOXDlR7cMEC17XzDlHDFrCgDE2aErXgr+5h4yefMKRJfe/t0/OvbZuCE9vyqbkfTbExtbsPc9plRGWvWc9Da0DRumiT5ypRHur6HrOego7m9pKuyV6XEd8DJYGvnbmw/shc7u/ZH92cLG83JBmTcHI5mekvmzoazUsNSYNOFcbQyqEEGXwg4nglQw+YHcc1BgBpmfZPHWOLrBRlUM1rJj46BBb7Hpi/n4aGtRwAAdz1zIGiaogfNoIYzaYfSlZqIRlfWy+Wb0+jBPxPDDGrCDvegBgup4Szk43QShCd9JAfZh0+FvNj2poSwonOQ8HwknINqWxZaJvD+U4AB6rDlgnK/hkSSK9x1IIsyEJYQUf19zfcRjJixLTvqjlssbFLSt+kFiIYUmhfNL3s9OwhmZGwG6t6u/AmlPfsEWEfyJb7FwUNBia9lGiWZRlyFpUGlJb75gGTAyRZmZURhw594BtUSGtNbk5gzNYH2pvzbQNa1cWL7LCTtBDzpI+s7QeCTHPGAbLjCQM2TPrKeg6YyDSr8oDTaK1OSvHbvJuztPYQ9PQfxQudu9GT7o8AzYSfQ0tCEvuwADg90x35mEJwLsxgSZuxHcvxHd8aNvo4CVAg40oUOyncUFJJ2/rWzZHYq2DNqPqASscuGtQdVStiWZRouxH7XJltc/9/9ROUUzfxxfRksJg2WewFSiSRc5ZcdKUVEY0tp0yHV9T0snbUIwOCfBZ70C8ZKBTUpUMoEqMfrOaQnfROgU836nQyyQZNMPza9QgXBqa/NgnutzULHs4n/COrElPh6Zg8qxwCMubCUIfwjtIQFpYeW4VNKQSuzZ7M4Wxayg/vNvLgLiXlzYMcypHFWFKDmL991NH+frfNPADrz7dSLyy8TRSW+nvKx/egeHMn0BM0VSkt8pVLRSuyBviN4oXMXlNZR0GoBBeNBemIBUHyv4pSm/AdEbzb/Idve2AqlNWa1TTclrcE+x3qv9HrStFLPeg6kltH+05LraBVlAXd27ccz+7cWPHdSKXRn+tCd7Q/GqZjXUlOyEY7vwYstWpgy4MKM/UgPV+9O538/HS0NwXGaYNyX5qRIKY2/Pc/FwhkClyy3sHBGsqDc2LbyxzPUAHX+tBPQnGrE7NYOJIMsPiCYQR0BWbfwfSnt+DV3HE/aCXi+h1wNzViIaHTlPDeYh52AJUSwOG4W9LYc3oXNh3cWXN+MqfMgdXyslIh6GOT3pR4/77BhtZev/EkRSI0lT3rBKMCgtDfsBB107lXKnKMNNsJsIpj4j6AOVFBe6EkfSTsJBEPtOUx97PjBH2hxgFpLuU0oXPVMDJJBVVoju3MX7AVzynfdVAqWlNBCRA2SNu13cKAn32SmY9Ec6J5u2EEWxPU1DpyxOhpJE8+gtjY0ozvbj+1H9prgRJsA1QrKjcO9Kr6SUQZmd8/B4E2rcNZamFmTSmPD7p7oZ8yZav7fdh18FmvxhhYTPPfFAtRUIonTZy/GrNZp0XMxHmb+hiM6BtxMUGJf7joyahoAADu7D6BzoBv9wb4NLyiD6XPSABDMUs0PUY+XUgP5Lox2vFvwCP/Nd2Xyr8GOlqRpBBU8Vl95yHo5KK0xp8PDhy9O4NLl+XKxMFi2reFnUNsbW7F4+olI2AnMbZ+J9qY2nDxj3qg81uNNpmgobdqVkDXsQQWAlJ2EKz3kPHfQ6xLR6Mp6TtAsz3z2xBdvD/R14kBfZ8F7ZXETPiAfTADlP28mO1MZprjwOQxhVZ2MLbYD+SkWMqgkLN72NBExQB0Gx/fgSA+JYAUtn9mq95EdP8y8Jx0FjLZlDbnLbFgmXC2DalkWpOMit2cfrHlzys4ttIMTR5VIAkLA8RS+cne+PHROu42WeScAAFr6zT40x9fonbsQL1z0WvNzfD96ATWnGnH67MVoSKTQOdANKWMZ1KI9qGEGNSFs5HynIIMaHw+y5WA/+h1zktzeJDCtxTxv7Qf24AQ1gE917ACgCzKoxQTEkEf5jAYZjNOZ0tiKk6bPK3sdT/lQSkYD0nUQ7IUBgS9NBissCY+XxOQzhvk/6PAkIxFlUEd+D2pxBjXc82oeT5BBjRpeefn91iI/p9Sy8q//4ZT4hpJ2AvOnzkZTsoHvbyMgU5RBzboyGI80+ElEWG7v+C4O9Xfh+YMvcrGAqE5Mea8bLY6GjczcIOgq/oyMFjdji9tKxbukh1tx8rcJP+MmOqVV2VEnaTcHx/fGxYL3RBMuvsfPXWzLhtIKju/Gtq5N/PBu4j+COsh5TjBiJhgFUeYNhkZXWPoYBhW2sCG1rKlrK4Do96WhowxFORYs5Pbvh/YlxPwTypajRPtPk+YDa+eRwmM4a1EjGk+cCwBo6zkIAHC84E1ZCKiwcUJRcD17ynQcSfdACBEExkFGNPbGFJ7g2pYF1/cKnhPTgdgELut2dUX3e9IsO5rHpmw7HPmKJckMejOVA/wog1rnSCUMFlsbmiruX/GDk4X8Xl5ZkAU0gauMgjwZyzwLACgKyMJVSys2x26k9w0VBKjNqehxAub17gXBNmBG3oSXhXNLtdYQIhagyvLzXIcqHGPDPajDV1zi25vz4avayrBSdgKO9JD1HWw6vAMH+4/icH/XoLcjopEXllgmrcLzP9d3o8+E4gBVBtt0QvFO8WGAGr5VS6Xw6M6n8fT+rWP3oEbJxoPb8eTu53A03VPw/aPpXgw4mRHvhH88yGdQ8+cubQ3N6M0NYF/vYWS8HDOoxzMzA9ULynvzJRr8Qxs7+ZEqQQbRsuCr2tuWhzNDhbDQ0dyOhmQKc4J5pXGWZcHZscf8jAUnli3Jy+8/Na+HHZ35YLc5JfD61U3AApNBnXpkN4DC7JYOs3JF+2dTdhKnzJyPxdNPBJD/IPNVuM9AISyQsS3bNNNBvmxQ5F+ZONCbLyGe025FmWA71iL/3KaeghLftKNw4z1d+MrdXejN5Bsy1bsUyZT4StiicnOFfImv6YZsMqb5Yzf3oaPsqipY4c5nnovvLzzJKLfqfSxcX0UZbtsSaGtMRONvAETdiPMNr/LZ4LDELBwNk4iV+a7deez7FrkH9dgVZ1Cv/00n/vNPDRioYUxd0k7Cl35U5eH4Dn8XRHUSzpm0CxYrlcmgBr0x4luNMl4OrvSjgBYIRoLExnjpoJMJYLrMp90cenMDY/ioRkdXpg++kgUNBwGgK9uLfifNxM4whOXRSitAaygl0ZJqQmtDM3qz5jVTsNVrApv4j6AOcr4LN5ZBje/1o7ERZpfCjJZl2VFJZy1U8AduCQHbsnDS9HmY3tJecj1LCDi79gIAUotOLHtf+REzQYB6JB+gvnVNGw72H8Y+nYU1bWoUoMabJIUZVKtMeXJDIoWGoPGSBUBBRw17ijN4njRda8OGXfGmSgNOPnBvSMVKoz0vClDbLFlQ4vvLJ/uxcZ+LTftd3P5EPwTEuCg9CsuorOJBrgHbsoPXh3k9OL4Z1xOfk+vLfImMUrqgYU088xyKuikX7HkeuQxqvIPvtOYkLEsEpWFhBjVsJa8ws3UaWlJNmNXaERyvCSCV1sG++Pz93nR/D9JOlbLtGhd0uNJ9bLJe6d92b8bCb55KY9YLG7H4sT/DdssvJljRCbCpkHB8v6a9q/XWnenDcwe3czwOTSr5udnhZ4EISny96LxCBlsyDg90oStjsoXNqaboPuINHcNtOvnFR7OFTI2TsW7HyinaPqW1RtbNIee7/FwZBk/50esiP27RQspOmu8Hzbcm+gxUgAHqsDhRg6R8icdIj5yg6kydfX6VaLgZ1MFO9Cxhwdm1F4mp7UhNnQoAeGx7Fl+9uwvrd5n0h13UwXdXLEBdNDOJASeDtsZmWIvmYerR0gxqvsS3+rELIQBt3qDCBgPx/ahKKzjSjQKvaGVWawzk8vedsvMNgWzfNREZgCQUsm7+uB7YnN878sjWXPRc1XvPSHiCUCmDumTGfMxtnxU1SXKlC1/5Bau1YZBvvpaQSkeLHbGaiNjPDBdEisYEjNDffFc6HqCa11G4Uhr+fMCMGWpraMHCjjnR+0/YxEhrBU96KN56En89xrV2HsTSP9+N9n07qx5bWELMBbjhy7rl/7Z3d/no2L0dDQN9mLV1Y9nr2JYNqUyGxgsWWibCievTB7biUH8XdnYdqPehEI2YMCiIFseDBo2u7wfnFSY7+tTeTXju4HZ0pnuQdrNobWgquJ98ia/5HA8DtZzvwAvOMSv1xphIPOnB8V38defTePHovujcK8QAdWjCxXIAUSdoS1iwLStaHAlH4U10DFCHwZFuNPoDyK+A1fvE/XgSZdHCQMuyC7q2VrOvJ4sndhwt2K9ZiSUE3F170bBoHmxhwVcaN/9PL57f7+Kb9/VAa50v8Q0yqP25fNAyq828RqY2TYG9eJ7JoGpdkEENO/8Wl/gWM5kyBV/6QeAZlvkGeyqVybJE+19izXP6YxnUVCK/9y3M/gJAUhQelyp6OQshoMZBt0FPSfixsTDFEnYCUxqao2YVju9FXXvzJb75/Z0KhRlUq2icj7l+WFYcOylRCls6d41Io6T4/tNpLSZAdaUPX5lO4eEHkun8Wvi4w0y5H/z+s0XNXgdy5Y9v3jOPAwDmbHq66rHl97Lw/W24ikt8Q1MS+e9PObQfKPNasoQV7TfyVGElwHjnysJxTUQTXVjGaxc11fOCz14VLIR6SppmQJ4LLRBVQgHA3CmzkEoksWDanIIeAoAZY+MGQchkqD5wpY+e3AB6c2ns7jkYLabbx/H812PhB7NOhbAgtakUsy07Wsj0lSzbzHMiYoA6DK5v9rQlgj0F4+XE/XiS34Maa5JUwxv6ob4cLv36X/CeW9fjvo3ZQTeSW0LA270PDQvnm/2oXuHvOO3oqIuvtBN4YHMGaSd/nYRtPshaU01InjQfKTeLtp6DkArwgwgwHDVj+YMF1+aDzAuC0XhZudQKEmb8UUuqMbh2vhttQQY1ES/xze9BTQiFnFu9iy9iQXG9FDfIKkfE5pQ6vhsF9QVNkhCW+/oFe3fL/0yzIBLvGt3vpNGfS+Ng0Jn5WHRlChskAcHJvZJoSCTzw7hj+67zj9WUmIWZdaULLz8yUOH3FbxM/VRD1WM7HscgjLRKAeqcRL6sVyiFxoFe84/Yc206xVvBPFw/yOCM/wwqYE5OJ0OzDqJQ8blHuFjpSC9aPHKlD6UU0k4WrvTQmCicn96YTGHJzAWY0tgS/X2Ef/FZ3zFJkKCsf6IK+zuEWeDebD+AWAY6/IzmwueQhJVVthBBd3cPKTsJ27Ki5o+VmkdONAxQh8GcOPoFJXbj4cT9eJKfLRYr8ZWDB6jf/fO26GTxV+tyg5ZB6EwOsrMLqYXzkLBseDL/Zvq5jm04Zd2DSOZMKezj+zRue6gvutwWgNLmdWJZFppWnQ4AmLl/MwDAC7KVYZMkMchJZ5jZ84N9pgUZQSkhpcIJU2ago2WquT+R3zsY34OatPPDwa3YbMWU0HCl2ZNZjilFMkFxd6YPO47uq0t5Tr5tf+U34bDsXgYnDOFsMKlMN19fyuhxFr9mwtLojCPx0NZO5DwZNUkKXy/TmqfAkT6OZnpxaAQ6qvZm8yciU5uT0XFJKdGYSEWVAaqgFDk8XiA8vekc6Cm576MDpa8rK1Y65ra0Vj228TL/diIr7uIbmmMXdklq6u3GzG3P4+RH/liwJ9WONWIx+9AnxmeN67sMUGlSKa7gCZvUuUGAqqExEASmrvTg+l7Fed2Aef9WscXTbDAlwpf+hA5Qo5E7wblxOHO8cAyKALgPtWYmQ+pHDRH7cgPQwXNpCxtKS/iqcnXZRDM5HsUYijIyKt7RE5wTOMbCZj1RJ1PLjJnxpV/1zW5bZ2FnvMFKfHNbdwAAkkGJbzxAvbzlCKZketB2yARqT+wr/LmppFnhCj+cGk5aCD/ZiJn7twDIN0rKN0kaZA9qEDh5ykfOcxAf/RGu6nY0TynbxTcdC1Ah3GhxJV7imwgCEKfM/EwhkF/x1BpPH9iKnd37caSoffxoCxcmxCB7LEQ0n9jsS1bB8+BJP8g85/eMe9LHQE7gnqcHsK/bB4I9Qf/4y1141w+ewD/85KmSVfOUncSSmfORcXPozvQdcylWPIBpDLocudKDr3w0JFKxPSeVM6gA0JXpLbnvkgBVKZz8yB+HcHSlJc80NOWaJAHALGECVB00/Grs7cb0nVuRzGUx5eDe6Hph+ZYnzXzfeJfQ8UgHH4iToUSRKK64gkcIAaUUPN+LFkIH3Axc3wSnjnTRYKcq3l/YWyJ8e/WCCj1/gpf4hgvJMtif6/k+LIjY8yfKNiSkynwVZk8tNCUb0ZdLY3qQkLAtC36w/5kZ1OOU65sXSMK2o5VhAVPiK5lBHTPhPpD4vkFLmBKHavtQu9KFK5KDre4PPPYUIAQaVy+DZdkIzzMbg3mTGoDt+9AAulXhKmlDQsCVpvwCAOxEEt3zTsWsIIPqlgSog+1BNSd+Ukp0DnRHb+xhW3uNwoDbvC5Rsge1KWWhJdUEaG2aJJkrIynM6zfnlX5gWIjP28x3lh3rFV5fFmbOqzGlV2F3RRmVwYar3OHrZONeDzff34LbnxjAV+7uglIaGQd44ZAJHv60+XCUeY0/v5awkEok4SofWa+GeSFVOH7+vSPrp6MGGabEN2X2HGodlCIXZ1DNwoVSChACdtFLujhAbcgMFCxMWP5gCyPs4nusKpX4TtOm+qJ/lpmT3DiQr8AQsSypacRi5jxLPf5LfMOFpHBvPNFE5kkffcHYl3CfaZRBhVm49cPO+lDozQ3Aka7pyOt7aKiWQQ16S2ioYIycjP7GJ3IGNWxmaKYr5LN+YaM3S1ixBnx8j6hFGPQn7ATmT52N2VOm44S26QCCRczo/IgB6nHJlS486ResUOQHLfMEbqyEgUr8ZN22rEEbJR0ZKBzloHVpgKq1Rs/j63DoN79H958eRGLJIqC9BQkrn0GdannBdYPbAOiRiYL7aUiIgmZalhDoWbwcHYdeRCo3EO1nrbXEN9zr7CkfCTsR7d8YcLIF+yPj1w/LZ+J7UGdPaTPHI32IoMxVwJT4AiZAzTiFr2WpAU/lmy4BpaWxYyFsVlTLCmFYmhp+IGqtTWlvePxKYvP+BH78SP42fVmFgRzgysLH35+TkLr0OU7aCXjSx1P7tmBn1/5hP65cLMPm+Bls7dxtmiRJiVTwu670ug4XWXwlYQuBf7hkasHlXemi+bpBEBSW9g6+MFK4R4qGrlIX3ynKvB/l2qYCAFKZfIVHIl7iG3Qp96UfNf8az6LsySQZlUHHt/X7tuCpvZvRk+0Pqml0YQY1+EwxAZnGgJPBkYEeSK2Q85xokbq8fJf0ePM+T/lwB1k8HM/CMWlh5QeQr0AMs4As/x8aN9zeFCyOdzS3R8+hLfLnv5NhBirAAHXIXOnDU7Jg6HJ+kD1P4cZK1FXVigeo1Tv59uU8dPYXBqgZp/QNcuc3/xNPv/OD2Py/P4/081uQOndV8EdvR/tGp9rBG27Y7EgDPUUZ1MakKCi3sISFvlNXwdIKJ+zZGCvxDZokDRYoBPs18uVFpoR13d7n4StZ9s3eBGUqKjEU0GhvNE2UbK+w3auNfAa1L1t6Aux4oqAcx1My6mA9VornkVZjiWBua7hfNwjulVLY322hN+NhX1fp/bgScIoWrnuyZi5d8XOctBPwglKund3DH6cRD1CFkOjNDZiukEG3w4ZECi8e3Yu2xpaK9yGVDyEsnLWoEd9+16zo+1k3v3jWdnAvTty4znx/yjQAgDXIKn3xHikaukoZ1GZtnnunxSwaxbOmyVwm+jocZeFJOS7HzHjSx6H+rvzJdfB3Oh6PlWioMl4OWd9F50BPSQVP2O8AyGdXM24O7U1tmD/tBMxq66i6BzXeNT5c2AHMrPbxXspfTRhsh3vnAURd9TVML4WRHtc22XnBonW5Bfrw3MSV3qQJ/BODX4Xiwj0G8X1gVhAo8I9s7ISdzOJ/qFawF6RS+dvhvtIyzHRRgJrduQd7bv4hZr7+Miy65gPw+vuxZ2oCKvhQKs6gAsFkCAH0qvIZVNuy0ZRIwbYsZBafBj/RgDm7nobrv8bcfgh7UBUQBC1WNF5EaYUBJwO/6PZh84b4yXEqaToIAkAiV/h85DOoCo5f+gZnxpcEHyZam7LXMV6UyTfHGjyDGu6ZBcI5c2Yl91frMrhvY3PF23UNaNy9ofDx92X9gtECoZSVgKt8ZNxc1ZOQweS8eDmnhCO9IPtufs8Lp82Bp3xTml2BFztxamu0kLAAX5nGVp4EUglgzqYN0fWz7R1oP7Bn0IURFO2RoqGrtAe1VZtFIq+pGVoIiNiTnMymo6+FEKZqREtIbY+7Et8XOnfh8EAX5k89AafMmG+GyQdNysYyQM24OSTtRLTHnuhYhZ93WTeLfX2HS+an25YNN9gqE/Y2UFKhKdWA9sbqDehC4bxyP1jUCe9rvP2dD0W4SCVjnXxV0Jk4XGTPn8Pww6UW0QJ9lfMfx3fRmKzemX+iYAZ1JJSZm0ijJ75Po6DEV1TPoHZnSjNF6VxhIHLoN/dAS4WT//ETaD55EdpXrwAakvCVhCWsaA9qmEHNHxTg6MI3jVQyX+LblGyEJSwkGpPonLMEM/a/EGVQwzmoopZSS52f2WkFpeVSKRzN9JS7hdkbm8kHog2J/Epb0jH737xGE/QkgwDV8TSyZcbNZN1gnIn0TUZSKWw9sgebD++setyDCctva+FJPwrQByOChaPwOVNKY8DNYv2u6hnDO57IYdeRwtdFT9b8XCGKS3yT8KSHjJet6fgriQcwOtjfHO9UnEokqwangBmXE89oNybzX4cBcLgYAgDZ9iCD6vtVo0+zx9XskaLhqZRBbRXmteinGiCThY1Uktl8BjU8sQu/Hm/9DjrTPcj5XtTROjo5DfafjYWMm8MTuzdi3d5NY/Lz6PgQziV1pY+s5wTdevPvl83JRqRd8/4vlYoyobUukoRbxPqdNDbs2wKpzcK71OO/lL+aeDY455vKNRmW+OqwSZIY0uf/8c5XflRVVYknfXbxpbwwU8VVoLERz6LFSxksy6qaQe1OuyXfy7j522ul0HnPH9G+5kw0zJ5ZcD1P+rCEgF8mg1pJWOIblmhalkDS1uiafTI6OnfCCRoXqbAEuIY9qOFeFUvke/QqaLjSx4JpJxRdP5iBGjs5bmnIv7ElgvE4XlMzhDBzUAFT4ju3Zz9+Pnc9FiTygVd/DgWrvFKbPXEH+48O+lxUorTCozufxbq9m7C/txP7eg9XrUTwg5PeWkt84yXJCgqO56Kzv/qH/qG+0sv7s6aEuriDbsK24UuTQT2WoppcQYYtXw41lG58JqDNPy+NyfzXuXC/c3DS1D1vEZzWKVHAWm1xREQLcDUfChUpN2YmCYUmSGghoBJJyGRhBt72/WjUjNYaTpilGadzULNu/r0iH6CakU5joSfbD8f3kPNL3+eJhivnu/CkB19KOJ6LPidd8PfXmEzBlT4GnAyyvgOplRlDaNVWUWM+x4Gs70Z/N0k7OS4XooYi57vR4lTOd5FKJM28WN8taJIEcHtcrcLXR6JCADq3fRaaUo2Y2tQ2xkc2OhigjhCW+I6dcGWuuJupLSxIJeFVOCHqKZNBzTjmPrTW2PbFryGzfSdOeNsbC67TmGyAgsliRSW+xRnUMuJNkpqSDbBgIWkDXbNOQsJ34OzeAyC/B3XQDGrQLVrFgvMwk9mSasKUoJxo11EP//N8BhnHlA3l3Pybf0sqH/CEGVS3yexrTCJf4vvyw89gju3gLW0Ho+vvOYKo6VC4Uuz63jHNMct6DrJeDgNuFk/v34JnD2xDV6av4vWHWuIbdjkGTICV8XJoaxz6cfbnSl9vgBk3k/XMicWxNCaIl/iKKECVJTNPq5FF+5CbUvmvs8FrwHbNyXvnKWcAQtRUXp4/heBJxHDFM+QtDeZ3OtX2oAHIVAoQoiSDCgANQUMrpVUUeI112Wytsl5+f3/0HgEddVwfbZYQcCZw11Man3KeEzSnMXNJ+3MDJddpbWjGvp7DJggLtpIMNYMKAANuJpoSYZqhjb+/81q50oMnfcxum44F005Ac7IRUitk4wEqkztDMtgM+I7mKVjUMXfQ8YkTxeR4FHUWZhi2HtkT1drT6AkzeMVlDLZlQaFyY4HuTOnKes4zp997bvkR9v/kF5h39bsw+82vK7jOydPn4fTZiwtLfIMM6v9kTIvvp5wpJfedtAUEBJJ2Aik7AduykEpoHJ292PzszS8AyJf41jRmJhhnFJbHhC3aw8Ak7Sh8+Xdd+K9H+nD7ExlAA1kv/+bfGAta8hnUIEANMqit2f4oFOn083sZdnTqWImvKug6ONwT5rDDn5QSPbk0Mm42yhSVk3+DrjWDqqIyqXAPqjOMisP+nCr7pp+0E1jUMdcEDcdQquT4sedPyKBBxtAyqCbLH4w+8D28q2knFiVMmWjO0xBKwpK+ydgFJ0/5Bl1VAlRuYThm8Qz5599oRspMtYKFiGC/UDxAHZhumlw19pu5trPbpsNXEie0TYcImn+Nt/K/TDCbGUDBuK+xyqKaig4PUk7s+ZE0vuR8Nxr55foeXOlj/tTCaqUT22dhRutUzG6bHo0yq/QZ1dzVidmbn44WpEWUQwXSbhZKKyTtRMFn10SU8124yseUxhZMaWyNKtxMo0fTET8/ui7/vkGVeSrMoE6OMTKDYYA6AqxgDmHGyWLT4R31PpxJr99Jmzr8ooDBElbVk6Fye1Adz7xB7v/vX2DaBefhpE9/tKQDWry0M8ygdtjmvu7PTMf7Dy7H5zqXltx3KmHehJN2ArZlwxIWZrQBvdPnQ1oJpIMAdShNksKA1A5niMGssu44ZOGuDQP4h/86HAWkj25zoLRG2sl/yDWn8s9Z2CXUbW6BQH4P6txsvmTXEvmg5GAvkM4FTQ60gtIyyuYMd15bGHB6yocX7O2p9qFs9qCajsqDiQL4WKMkT3rR/NmhGHBUSXlvqKWhCUJYUVA5HPES0ISto1KeoWRlfZ0/xrkb1+E19l780/TtsKHgOl7UtVkmTcYOyJf8Vs+giqiJBw1PPIPakDCvkal2fv8pkA9QtRAYmDHbXHfABKgtqSacccLJmNE6DbZlR1ma8SBcYHJ9UwYZ7sGT8QB1DE48w7EWx/J+RFTMCUpVfenDVT4Wd5yI9qbC5kdJO4HpLVPRmEhFSYpHXsji2v/Xid88VZhxXfDUXzFt705M3bcTQL75IQAMuFlIpZC0EtAYWn+G8cbx3KDjbPAZAzMGpSvTGy2qh7PdtTajeR7esQHbjuyp85GPX9EcVAaoVCvzRqKxp+cQjgz0jKssqtYa247swSM7NqDfyQx+g3GuK9OHrZ27y3Yysy2r6slQT5kMatbTGNi4Cc6BQ5j1ptdEwalQErO2bkTHrm0F1zcBqsapKdNhc7fXhBe8VmR0uTcMjaRlB9lTG5ZlYeYUBWUn0TNjAfSL5r7VEOagIujaa0VdfDW2HZL40cPAHU+Wlh4BhQFqa4N5fO37dqGxP5iHWZRBbffS0dDLZFFZZ2e/GdUig72dYROU4b7mfeVHv7Nwtm21sqa0l4XjezV1zA1Hc2hlmhsprYLmT0PfLdqfLZ9BDdlRtnZ4J+I5Px6ghiulQxu47UvPHKNSaD1yCEIAS1Jp/NecZ/DaFx+E7QSNKmKZOpkITh6qzdsThfNvaejiGdSGpPl6muUBOijxBaCCPaheUzOcYC5q+DcKIFp8SFh2tKgzHji+C0/5pvxf+fCkH3XxBcyIorHYS+fJsJpj+O9HRMU8ZUYLSq3geA6Sicqluw2JFBZ3nIhTZy7E9/7SiyMDEneuG0BvpvRzIVwwDJsfhos8nvQhkB+TVq+s4o8f24U1N9yPG/+wZci39aR5HxBCRJlkqSX6c2kcCQLU+CK70gq7uw/Clz729h4e6YcyaYRbJ4ZyXjCRMUAdATnPQcbNmcHKcnw1aehMd2Nr5y4c7DuKzoHueh/OMdvf2xmtMhaX0IQBScUmSeUCVFfj4K/ugkjYmP7Kl0Xfn/PcU+jYtR2ztj5XcH3P1zjBdtBheehTCez2K29olFrBsmwk7ARsYcGCwIw2c6LWNesktOzbDl/qKIuVcKu/bvJ7TnXUYKA7LfGLJyrfTgNIO7E9qOH+t/27AZhSQq+pGRD5YHSanx9vkRKFJ5ZdaY2c50TZQlOiK6M5Z0MVZlr84AOt2smsJ32knSxc6aEhUbpfr1jYJCksldUAsl7147Qr7LNMO9U7B1vB4shwS7Lie1AT1uB7TQBTKnbC8+shguDSD1r3h/sWASCtbMxP5NAoHTSk+wHkAyKg1gwqOOf5GGiti36/5v0p3MfuB6/lcOHAa2yG02qaXKQyAyXdqWxhmQB1nGRQneCkGjCzkR3pwZVetIiox6ipkx+Uvx3L+xFRMc/3oZTEtOYpmNE6DSm7+uJoS0NTyQJqT5m54jpY8AwXmt1gwSlstGRZVl1nhH7+1xvR2e/gO3/ehh1H0oPfICZctIpn+ma0TDUNHWONzMweVPP5kvPdcXXuPB4NZYvTZHB8PMpR1pyKtRkfZw0sMm4O/U4W/U4GfWU29080DYkk+p0MHOmVlL7YlhXsBaytxDeVG8CSb16L/T++HbPf/Dokp001P6O/F1MO7c9fMfZzPAksbzDP4/NuK6pl46TSSFoJNNhmBqplWUglFKa3WuiavRhN6R7s3X4ITksrlJ1Aw0AfWo4eqnh/4V4VqRV6M8AP/2Ljc3f041Bf5cBBqaIS3yBAtYOGJodPXQ4trFiJr8ZMVTlA7U7rIJsmo3Jjc1J4bCW+bpB1UVWCvH4ng6znoDHRULHcNk7EmiQlgrLITJnxOaG/aT2Ae+c9idNT/SWXZT1ddfi1JSwo6GH/7cczbEnbfIjLQT6Ipu98AVP370ZLdydmtU2HbdmY3tIercwDQFsQDEEDyWDPcfkM6mBdfFniO1yOn3/NJW0zsidha7QFe1Dd4IQ3rGRwWqdAJZLwGxohlCoYNwMEGdRxtM/SDWb2Agj2eLvwg4HySTsRLWSNNk/68LXp8u1KnujSyAgzqDNbpmFm67SablP8XumV2Vaig/d2AVNl4ATv247vorWhOcqg1mMfqi8Lf+ZfttSW1cx6Dg71d5kAtahRVEMihSUzF2D+tBMwpakVLamm2B5U093X8fh3W0mUTReYNE2QBnN8PMpRNqNlGua2z0RrQ/OYzn2rRVgSkPVy6MulJ/xJpifNXpD+3EBJps0K9gFW2oPaWxSgrn74p5i2/Rk0zpuLhR95f/T9aXsL9xGLYF/VM3sc/HVbFuc0mn1hG53qQ7h9ZZodNCSS0R5UpRWmt9o4OuskAEDPc1ugkil0LTwZANAWD4yLRBlUrXDP0y72dg0epPlKYyCXfz7CEt/4fsTwgzIhFKZaPhq1H+XKGoRCR0v+baIrrZF2c1H3YBnt+Rrea94N9pTmgoC5WgZ8wMkg6+XQlKptCLUVC6xsy4JSumAvYLGPTduFBqHwtljn4pDj6ar7QS0hjmn8R0GGzRYmA6UVElX22qYyZiHB9jzMap2GpbMWImHZsIPyxuJXR7jnOB6ghk2S7CoLDPmBRhP7vaNeCsp7Eyb7mbSBKUGA6ljm99E/cw72rD4fR04y+9mdFpNFDTPfIduyg0Wh8fE5E2ZLAcD1XVNNFPxdJ+2EmdVcYdGwkq5MH7qrdPMux5Mm0+UrCbdayTrREAynrLL4YybnaSRyWSxY+3D0vehz107Akz729R7Gwo45OGXGfLSkmqJFz3qMmunLFf79/HlLZ8l1pFLoyfYXnFM+vnsjnj+0HYf6uyo+Z+2NrZg7ZaZZ8I1tH3GkB4cLSxX5UfOt46O8F2CAOiJsy8K05ilmtXgM577VIppHpxWynoOMl6v3IR0TRwbd9KSPE9qmF1xmCztYrTfP/6+e2os3fudh3LFuL7TWODKQH4Ngew6Wbvg9dqy+FOc98Fs0zpsbXZbKFGaaLSXx9B4HX7+3G/39Ll7ZbJoI/TlT+POLqWCOZdJOmMAhyOilbIHuWaaTr/vCVvO4gpNRu8reqTBMkEqis8ysznJc3zT4CbU0mD2KtucBIt8wRwgBG8D8ZLYgDEkKjTlT86ugPWmgN9dvOilDw9dmQaZa591qwgxqOKKiWgY855sh6Q324OW9QKzEN1gokFqiUoVvCvnn6IBfGgC7vq66ahkuPgy3HCsexLQ1mEYb1Up5hJJRRrS4PLfca0gDUSauIIMafG151QNUDXbxHa744kND0gq6dAKtUYAa/H1ZFtIzZkMF5YFui1kAS2XKBKhajZuFULPn1ASjrvTQl0tHJ6d2+HcxhCyQJ308vX8Lnj6wdUjH4Ss/6B7sj5v9uTSxhV3mNfSQyiqLG/GlHYVZ255Dc09sZnhsT/kpM+fjtNmL0NbQgsagq7clxJiVxxfrzRZ+Hmw9VFpV9NzB7diwbwsO9B0p+L7r++hz0lBaDlrpZKFwVrnje2isYfvO8Sgq7z1OsqcAUNugJqpJ+GE8nkp8PeVHJzIyaEQzkZlyMh9LZi4o2YdoWSaL5SuT8fzk7U8DAK79xdNYPKMZR9MmiEpYwKy9zyEhPWw/9WXQurB803adgvuF9PHEdg+XNh/B26fsR5NQeNZpwx6/qeqxnn6iRsJOoCERlviakp1kQsBtbEV/+2zYW81JWHhSWq1ZTXiMUiv0ZmsLFlwpCkp8Wxqsst1cYVkApBl9oRGl3xqEwpypCTy3z9ymO6OR8z0gCMaU1kh7OfRkSz/AahE2A/KUj9aG5qpdfM3AdInWhtpWEMPGSAoKtrBx2qxFENID0Fty3bDpFQD4uvQDwPGrl9XYYQfpIZyI5zyJXz21D3OnNhYEqK2NSWTcNCxhVVwtjZd9Fr9momCz6NwgUSZADRvz2NVKq9gk6ZjEf7eNCStYMBFR+XVWJFCuJiBctEqlCxfMEpYF1/fHTQY17OLbnGqC63vocwaixRVrGH8XaTeLnOeY+dO6enOykuNQKmreRnSswvL1oXZNLQ1QNRJOYXJAxP4myu1rtYQ1ZuXxxYobSsa3KYS6sn3wlcSRdA/mts+MXdfcVmk9aLf98Jzmhc5dyHlO2fn2ZORnwB8/zw8D1BFkWXZdu66VE2+2Uq9ykZEUjjIIW5fHhRlUX8mCrAUA/Pdju6OvV8xXSP5pPaSdwGlLToDKOrCb882OEm7Y7TQJ2/Nw6/9046/7bfxx3otoEAo9KoFvdi+seIwXLm3C/I4E5kzrCrr4JmEJC0krAVsIJIP37K7ZJ6FtmwlQ83sBB9/L6UuF3kxtv0fPF0VNkkQUjPixQEVbFiBkVHYotYlvUkGAGuoaAI72e2hq8E1QJkznwb5cGtuO7MEpM+bXdFzR8QWvz1NmLICGxr6eQyUnl1prfPt/tmHt7v1YtdDDrLbBO/iGlFYYcLKY1jwlKqUqZ2ksQG20Sv9+HR+DNkkaahffHzy8A18r6pAoADQnk+h3TBOqygFq/ngrZVDj8alSgOpPQycKA9TwNRAPUFMDfWjuOYqeExeZ7HqsTRINXbxDcyoRZFAT+QxqDuUDVL/BvCclihbMTImvM64CVF9JtDW24Ijbbcr2lRkFZYmhN3oZCPaap+wUpFKw7MFPyMJFLqlV9B/RsYrGfQ01QJWF75UZVxUEpMDgXfstYQ2rPH4kFGdQ3TIBKmCaooUBpeubGcQmkDLBlFVDMBVWhb14dB8Sts2tJBX4QSUkS3xpWGxhQerxuQc13AtUr45wIyFsXQ6UDxbC77m+h95c4UndQ1vzZShL5kicuGsDsPAUfH7OHixe/0h0mVAStudBCwG/oQkawN5OB81CoSFoGPTOA6vxgld5/+n7LmzHxcua4fpetAcVAJKJJGzbRsI2b8BHZ50E7NsDmc5EewEHm4WasBPIuAoVPi9KuH5pF9+wW7CM7eUMGyW1ByfNvdIcT0ooTGm0sHSOeQxKC6zdYeGUGfOjfahtjS04NHAU24/sRdcQ942FnTdNtqX8qJYHtx7B1//4Ah7cMoC71ttI1vgGnbITGHAySLtZtDea35dTYQZqh50P0JpE6ZNrekYM0iRJqyGdTBQHpwCQtAHbTmDJzAU4Zcb8iiVS4f5ToDSDGgabh5qno0slsTfoNG3DdID2U/EMammAetJjf8YJm59Ba6fZi5vf+8wTh+GIz7htSJjXeEMCaBXm+2ldfp240nvCeBszE1a1NCUb4EkJrRXcoEFKvtFL7X8XphmaC6U1DvUfxeO7N2JgkBFpju9G+0518L5EdKy8EcqgZhwNUfT+WRywFgs/D+vxWi4OUMtlUAHAl3503uVID26wT9JTMhglU73E1zTgM+8X4cxXbiXJc3wXu7oP4K87n8aurgOQSmLbQYG7NgxgIDf53+MYoI6gaA7nOCqjDVe3k1bimPbIjQdhgJqwK39YJO0EfCXRly0sp4nvP21Od2LqoR2Ye5rZB9qUzZfQheW9MtUAlUgAWqPRklG2o1Om0K/yJ5SNSYFXr2gu+Fk5z8ELnbugtY72oAKmjCdhJZAI/uqOzDkV0Bq965+JSnztQZp7nDpzIWa3Lqh6nTjXF8i4hQFq2MFXFmVQhUDUWbRbmuNJCY2kDVyyrCW67q5OG43JBuiga+2cthnoy6XR5wwMuVN0OPs03K8mlS4pB/zN+n3R1zs67ZIVROH7JaM4AKAl1YQ57TOxdNaiqJSoUoA6zc5/IDeK8n+/nhxsD2rl8uRaJWyz16khkYr2IpWTqpJBDQPWfR3z8eZ9Z+PR7NToMo3iLr7m67bOg5i95ZmC5zHhmr8h7kE9NvFqjlTCBGzNKYEpdrgYVP79TFWYUWtbttlnOY4yqOEiaGMyhazrIOs7aEo2mMqCWOVOzpN4YkcXnCpdo8MSX6UVth3di/6gOqOaXDDWwmSdJvbnHI0fbnD+dMwBqqtKMqZWDRlUs2Ws/gGqKxWUKn3/96QfZVDDzr3hQmYtjaVMgIr86DjNz5m49fu24PmD27Gr6wD63QwO9Hj4cTDz/jfrJ/5UjsEwQB1BUYA6Tkp8/aCjIYJhyRN9ZTnrOfCUj2SZ8t5QwrLhKR+9WafydZ55BgAwZekSAIVviAnH3M5PNUAFszMbhYoC1AGVf8P96KVT8c13zsRb17Rh9hTz/cuWN2Nfbydmt3bglBnz0ZhsiN7Ak1YCCWHBDjKoh+adAW1Z6HlsXcWT0WKWEOircf8pAGRcgbBjfNI2J8gFe1AD2goyqEGg1qfyGdRkQmDRjETsPs1jnTNlBma3dSCVSGL+1BOQdR30ObXPS8u3TRewhCgok/Wkjy2Hd2HAySBZVOIX3y+cSvfj1L/cg9kvPAvALDCEZdJCCExtaitode94FTKoVv4DuclSeO1qB285qzBLLlW1DGqY/a3+9+X6Cn95oRNd6fJ7PhM2amqCkMxUK/E1993RYTKnaV14klDYJClfLj1tz46Cva0qWAgyc+R50j9chSW+Jhvd3CDQKszvrcerEKBWyKCGnzPjIUDVWkf79GzLRmuqCQNuFlk3h+ZkY6y7tXntfPgnT+Fv//NRvOsHT1S8z5xnmqGpoBohE3QNrybnmZLnhkQKUpcuchENR8bNwfU9pIbYuGeoe1DLCRc96/G+WzzxADBBarH4ntGc58LzvWgxSmpVU5MkHYzYaUikWKkTE8593350H45meuFLH3/ZnP8s+ePG6lUlkwH3oI4gW9hQ46jE14tW/6ygTG9i783Jeg5c3y0Zgh2XtBPwZfUA1drwDHIt7WieOxdAbBVK6yhr5Dc0AMEbb4NQmBLsSyzOnjYkzXWue8t0HOjxcWIH8OKRI+honoLTZi1CUzK/tzWVSCBh27CCElI/1QTvpKXoeWwtlP1hc2wyyAZWeWPvqXH/KQD0ZfP30xLOQM1mcWT3AehFS/IP3bIAkZ+b2RsPUG2B9qb8SXQ6ZxogTG+ZGn2vKdmAg31H0J+r/U0z3zbdHJfZrwZILbHl8C4cHujCkXQ3UonKb1MtRw9DaI1pe3bg6IJTcMojf4RMJrH1Fa8te/14BnV6q4WjA+a5XNAikRCA0sCqOTZ653lYMacVG3braEj5Q1t8vOO88vNQLSHgawz64frJ2zfgrmcO4KSZLWUv78uKmppEpKo0SbKDJklWYwodLT5yqjhAbYh9XXji1dSb7zIZ3q/JSg3+2Ki8XKzEN2ULKC3RnhJI+RoeBHrc8n/rUYDqF5f4JuApH67vlTR4G2t+0HhPBItMLQ1N6OzvQtZz0ZhsgKf8aGvJgOPjfzabeYpP7OhC1pVoShW+Nj3pB6OnFGTwest4uUEbg+R8F67voSGRRNrNcjGFRkTGy8HxXbQ3tw3pdsV7UF3Xg43CoK+WEl+pFNxgBFhvdgCNyVRJc8jRUJxBBQDHU2gMGmhIpUpmlud8J5plDpgAdbAmSU2pRhwd6EFTstH87ToZaP7tAjAZ6d8/O4C1O5txyTIL/e2ZinuBJ6uaAlQhxOUAvgnABvB9rfWXiy4XweWvBZABcJXW+qngsp0A+gFIAL7W+pwRO/pxxrYs+EH9/XjgBfPp8jM4J/Ye1JzvwJF+2Y53ofDkrd8pn6GyhYZc9wxyy86CZZkTO6WB1sP7ccKWZ6NVTj/VCCso1W4UCggyqP2xk/2knT8xbEpZOGlWCkfTPZjS2IIZLVMxu2gMTljiK1UG4Z9edukKDPzhl5COA5VIwPJ9WNKPSn7L6clUf30tmZ3E1kPmA6Y/mz+xa22woH0fj33x37H/sfU44YENOPW270JYVrQHNWyS1KvCEl+FhC2QSgi0NJiGS1IDAzmFKbGgNZVIQkGb7IfvVV1ECJVrm24yLhpHMj1wfBeWZSFZNFam0kn57K0bTXsFx8UzexysnF9aIhvPoL78VNM1uDutMNeSsBwBSwCtCfM3ogE0JfOP8b5nHczvyOLlpzYX3220ADTY39ddzxwAALzYWTnTPGiXPq2RzFUr8TW/e5VI4qqXt2D7wweiy5QWUbYeKA1Qm3u68schwwC1tsdG5RVnUKVWmBH8eQwoG2m3fOAfVVUU/36FCMp8ZTBTtX7rzNEiaJBtb0k1o1N0Y2pzW7SvPGxct6PoNe9KhSbk/7601jjYfyTKDId73HPVOkwHwvLCxmQK/blMXTqf0uST8XJwhjDaLOQW5SgOH0xDzdcFGcXBAtTmVCP293ViX89hpOwkth3ZgxktU7Fy7pKqt8t6DjoHujFv6qxhd8QtG6BKCcC8cYVl/RrmP8A8V67vRT9TKTlok6QpDS3Y030QrvQwZ8pMZlABbDs8gA//ZB3292Qx4EgAFu7faGH21B44fhLVemFMNoO+eoUQNoCbALwGwBkA3iGEOKPoaq8BsCT47wMA/qPo8ldqrVdP5uAUCMbMjKM9qF5s/4QlRNBNceL+8Wc9B16Z4GfOc09hznNPAQCStg1fSvTnyp/UnNCzG+poD+ZcdH70Z640MHfjuoISHJlqgLJNiW+DUNHezIFYBrVc4sLM8WpAe2PpiqvZf2q65YbSJ50O7Uv8/+ydd5hcZ3n2f6dOn+27kla925Zc5G7jCriAMYQWCDUJoXwEAiRAICSBFBJaIKGGkJBQTTcY996LbFmy1fuutL1Mnzn9fH+cMmd2ZlVsGVtYDxeXtTNnZs6cec/7vs9z3899lzdvnxUxmRlR0aOZ8TfXdrK8r76YRhHUZExg7PqbGH7kSRauXcHoQ48zdce9QN00vM2nuuZDkSQ3VB1uT9Y3k7kWKK4kinVa+RFEK9l0x3U8BMRxQrl6Y8b10CJJZlTcJzM+gu242A58/dYpJkut1Hjrr40pAq89K8OfXpxFjfi4eoUJAVyX5AxLm/++t4hlN19/AeGwImRH0ltz2kLrsBRfRashRPqBZio/BwiqLSucuiDGmsX1hLrkyg0D153Rzx0II3nv6133QCTpxKb/mUW0B1WRwHFcOlTvsZIjN9hARaNO8bWbeqwDoaRtY/vYNXHgeSseeD1ndoiUiILA0q759Lf1+n/Xe0L3TJRnvLbxnPdND7Nr4kCIGDk+jdny0eJDRc3UMRyLmKIetZr2iTgRrcJxHWohxffIleMBzBkU327ZwLIbddAFx7+vZ1kX0rEkMVllqlpg7/QQw4UJpmuHFyFcP7iFXRODHMyPH9U5RyM/C4IahOVY2K6N49TXhZqhodlGyNLzRJIOvZYJgsDy7oX0pDvIxFO4/v9ezPGxn29k51jZT0692D/Z2p3ikOG6iMf5mn0k5ZVzgN2u6+51XdcArgNePeOYVwPfc714BGgXBGHuMT7XF3yIQVXbtl4Qjd7RBn9BEHGc478H1atm1hcL0TRoGzlA28gBBNsOrURKWusNzYKBJwE4+ZoLiAW5pgvCjKKCFYvjihK4QQ9qM8VXa9HPGKAJrWipqix7SapUf11x4UrvvxufPmKrmZrR+jdc3C2zok8lrtQTkGIUQZVs9n/1v+hctpAr3/tGkv1zGPzWdz3lPJ8GXqf4etc4I1qcu+NB+nY8RXuy/l6tbG6OluIeyqZHaEBxJcZQYQLd0tEsA0WUyM2ga5ci6nUz/TuD4R0XbDYONvb8wIwEVfauk2hbIVoOnniFIHjy90mlmaI0PVIgOd1oTi74BaBD3fdV4/Cb5stO0Q9bdVaq3kbfjCfC8w/CdRx23/84W+97AssvwSyeW/frLTiHRtuiliaibRMrFVi84SHaatVQZfFEHF1EfVBlydu4tdXy7HhgA6MDo7MXnAQh7ANupeRrOhb7pofYNTHAVKXZ2/d3EV5BanZvvlDd2rEPmaA6rsNgboSRYhRBtcP+VqNFv+3B/DjjZQ/xN2wT0zZRJSW0tTkxVk/Es4maqaNbJoosH7aXcmbMFOPr8VXio0JDsUqJlffcyLIHbydezLV8n0wsSc3U0E2DvFbCtu3D9p47uL4S9uxtToeLXAuNhKiSb2C/E6x5tuOECGpQLDtSm5m4otKVag+v8YtdyXfDYOu5fEX3AkTh8Ei+mS8w8rNfU7jldtz3fJzYf3z9WJ/i7yyOJEHtB6ISegf9x470GBe4TRCEJwRBePdsHyIIwrsFQXhcEITHJyYmjuC0XnghCkK4cdCPwM/yuY5A/l8WvQn2ePdBDYQwlEiCGhV1kUwjRBbKs1B8e/c8ibJ4Pol5c+lUIhukGcdZPoIKMxBUX3AmJgss622uqgbXuxUN2aP4SqGKL0At1UZ8QT/FiJLv4axmqrNQAtN+j2k0QZ0u1z9s7mO3og+NsO61L0eURBa/802UntpK/uH1uH6ls07x9RKZlGCTqRToOLCPNbH6BrMVzdhDUB3MI2QQWLaF41vMBDG/rQ8Eb3OgWQaKpFCsNf6Wf/3TSW7b7NEFA7TQSKYa6q4p0W65qSjV6r90OuY9L/m2OwGkLtgW4KkLzuyRW6mUecm2e1i44UGkCOIuCgGCOvvCWtIO/btesDyOInNYWpaxf5BffPa/ePgXd2BbdoPy8/4vfo17/vfX3P+jm9jz+a8CoMbrYzFAxo8k0pOjLHn0HpK5KdYND5+gXz3DqEUSVEUGyzIpfOqTPHTdTWz58teQNq2f9bWz9qFKMpZtk6uVqJoamvXMN6PPJuosiNa9ZqIgYvsb2JkJarSfarpapGLUyNWK6AGC6rqhzYdpmw2bVt0y2DkxwNaxfZ5Qk++PrUiKV4x1j++17kQ8/1ExauiW8Yx6PmeKJHX74oNjYl14L1YuIdo2ilYjMzbc8n2SSpyqqYc2S4ZtHjLxrJk6lm1Rs/TDt4ocIg7mak2PRZW3Tcen+Pr3Wc3UQqZTtAf1aCnGYaH3RY6itgrTFrGd5usZL0zTs2sLgmPjmBZb3vdRdn7iH9n4gU8yvHM/5nHct3oko6dV6Wjm6DnUMRe6rrsOjwb8fkEQLm71Ia7rftt13bNc1z2rp6fnCE7rhRmqrGBY5vO2YYiGYVlYjoMsST4F8fjtI5vNA1XVWiSort0SrZIsg/a9T5M8bx1Qt1SBZpaNpcZxIxTfwLPwjOUZrj0jxUeu6iChNt8+AWLdKkGNyzFUWUGO7OUMyyV7xqkUn3wa29/kHc5qZjaaR3dGQrDtOjIcCcnU6brxB2TPPI2FJ3n2On2vuwa1p4uh7/0EVxQQ/O8KdR/UaFwi1XsZ85VWFF/pqFSsW21u44pKV7KNsl7Dsi1EQaCkNxZ7HBd+9HCJ6bIdIqiFuQsaNrAJwaZYaz7HXKV+bp1p73MD1NCIe8JFom0j4FVyo8k+wHvb63U4Ra8v4nWv0Nnvr9lQ/SBSsUMnp9X9g+z828/ywHs/zuTgKNtuuIvHb7gH0bKIlQoUNmxi8L++z6oLTmP5S9Yx8pNfYU7nUSIJ6pipYs2wCxhcd0HD35bvjxst/gDHvY/y8xETJZ3P31L3u1VEqN39MMbBIS548ysQ2jqYc8uPZn39bH2osm81o5sGpm0fUZ/mcxF1iu9sCGpdnG/mpjeKoBZqZcr+/VSolQB8gRjve1tOI3IU/G3ZFmWj5tld+D2vv0v/yIHcCA/vfypsRzgRvz9RNTQ0yyD+TBLUSBtIe1Kk20dQH6e3ab4Fb81phRrGZBXdMij46vi6ZVIzm5lBQRS1ClVDa0Bay3qVHeMDRzxGdctmrNSKfRSh+NpeK4/jo50VwyuSxWQVG+/eEwTxqJHnoDD8Yi2EHgo5LmtOU+EDYPH6++ka2E3b8CBj199IYf0GznzN5Vz6uU/wR5/9IIuuuey5POXnNI4kQT0ILIj8PR+YWe6Z9RjXdYP/jgO/wqMM/95E+4G99D/1WOhxpUoKhm2iPQt6xbEKy7Gw7XoParRf4HgL01d2nFmpVyJ+kJJpeF6atkOtRYLaPbITyTJInnM6AAkOkaDGPJsZgLhokxEtZAnmz0ny2rMyrJrbetGy/OvdSrgkrqjIkhxSS8FPUE9fgzE+STnvbcwOR/GdDUFdldRYec+NXFrZ1fzcpluQclMs/tB7kf33d1MZeq5+Gbn7H8GckQRGqaDB2fZQX7QKLZI/SRCPiuIb/qYzNrdJNU7ZqIWIf3kW5HG8VE9QK529RPOulGhTqDWPgalIYt2R8hNUf2NsJiMJqr+wRumZKcHi9Hi9ByiKagkIIbVwtigeNkEVZq16u5bF1g/8NSM//iUdK5fw2k+8i8VXX8rG2x6iMDZF/0N3seNjnyExp5cL3nglJ73m5TiazshPrwdZDn/Emyo9TQbf1c4ecguWhn8bqUZ7HYBSIn6iD/UZxA8eGWj4W5ZcKj+/meScXlacfzrmBS+jfe/TVHbva/n62axmwNusmo7loSrPG4IazMuzJKii6Kt92k33cXSzVdQr1EyN3nQnmXiK3nQnDm64yfZovvX7J9BX0C2DfK2I6VihV6X4O0RQ900PUzFqjBQnD3/wiTiu4lghqG0JMaT4Tjqq1zrkh+24GJbLPVtKfPS6SfZNzFD6FQS6Uu24rktnqu2wCGq+VqJiaF7ftn+/bDi4naHCOHunhmZ9XTSG81rLtthoD2rFqKHbJq6/RmuW7ouUxXAd1+8/PXoxn4CJ9GKl+Jb02V0QSrrbMkGtFstolRr2+ASD3/wu3QvncOaVF7CqTUZNxDBi8RbvdnzEkSSo64EVgiAsEQRBBd4E/GbGMb8B3i54cR5QcF13RBCElCAIGQBBEFLAFcDmY3j+z2u0D+1nzo6nyYyPEC/mAVAkBcO2nhX//1hFneLrq/hy/CKoluP1PMw0zJ5J8RVFCXsWBLVrdDcAqbUng+OgRIi9M297W415CKrb6IMa9Y2cGUE1UZZaJ6gAsiCSidXVZU3bJbvuVADG9wwCkB0basiYM6MH6dq3E1mrguOgzZKgnumMIbguq/IDnBkrcE1qDHCRTI21j/wMd+0ZdJ19OoLjeAJQkkT3FZfh6DoD2xo3yFVHwpxBjGhz6glqqz5YSRRDxc7papHNI3ta9ssUamU002gpkgSeOERfptNb6ByHyiy9m67rNni6fk44k+DIpI+gHpg2+cdfT/Ff9+QxLDdEVQUB2vyeWkXzElTDT1AFx0F0PZpRlJZ7dryAHCEfSZFCgicGc2gKbDHyXhet6Ob2DzeSSZKHQFCHvv9TKtt2cvLXPsfFf/cX9Cyay+o/fTOiJLHh5gfY/eCT1PYPsvav3osaj5FZuoi2s9cx+rNfY8QSlF2ZvWaC9VpbU4IKhP3PAEai2QJH4ISS7zOJW7eMNvwtjw9hbtrGssvOQxRFRk46H4Cpu+5r+fpD+SOXjTrt77lGUE3bYrKSb3o8vIdnRVDrc0JJb/wOAYLquA5FrUzV1OlKtdHf1ossyaFIkizJaKZOQStHXuutB7plkKuVGtSM657EvxuhpBfCWn8ijn1UngWCGhVJaosgqOOmGgoSAqFHeUxwmCzbfPX25l7UudlulnXPJy7HMKzZE1TXdZmq5inpZUzHDtvMgkLPkSKoB6ZbJ0lRH9SiVqFmaLiuw3fvn+Bt39nC5qHAy9ShaurElWYV/cOFAIfVcvh9DNd1uW3rLh4Z2DbrMWXNaeptHv6fH/L9j32Z73/8y9z+nk9gjE1w7mtfhiAIWI6LacPPtwg8tKd1j/MLPQ7bkOS6riUIwp8Dt+LZzPyP67pbBEF4r//8t4Cb8CxmduPZzPyx//I+4Fc+GiEDP3Jd95Zj/i2eh8iWS8zZuTX8O6hwq5JMRa+hvQAoP4ZlYvpJnZc8Hb/UCdOnlMxMZtQZCKpH8RKptaDBdo/soprtJtbbjWQajemX69MrBI/q6khyiKCqghOKBx3K/iUoBhzKBkcSJbLxOPhopGlDatUKxESckad3cerSPq/gUcqjZTuIlfL0b34CgJ4928jPW0jV6Oeq1AQucGulTodXUjEoeJP8l3u9iW7IiqOvv4dkJY/6zneF/ZaBvUjbWacjpVIM7hth2RmriY2N4rpQcyUMV0SJKA6nbA0RFweBWguBKEnwVHxrps6+qSFqlkFnMsu8tvo5Vg2NJ4e2gyDQl+70bZCaF7L2RIbx0jSmbc0qCmU79STRVlU2V5Lc63RxeXKKS5LT3FDt4pt35hnO2+wZN+nvqE93bQkR2bcZChHUeAJHkhFtC8m/T8oRZPn8RN77hwsIIJr1547EZiaa7GbiMiv6GpWeRcFtKMA4psWBb/8vtb0DTNx+D52XXED3lZcjbvUUq9XeHpZecTE7b7qbnY88RXLpYuaefhLs2oKlxpj7xlez/aN/z9T9j/B5/Rz2TJgwy28XHdetEFTJT9hPJKhHFyv7MmwfLYV/u/ffBcCq89cCcDA1j2TvErJ33s/Cd7+j6fWzIahdqTYqRo3uVDtjpennnLHz+IGt1EydU+etoDvifxwkqOosm/jQEsduRlCDBLVqaGimgSxJIUMmSDJN26Iz1UZRrzBVKSAJItl4OoKgWuSrJSy7EUH9XbSzeEJMzguinedEHH24rst4OUd7It2EkrquS83wPFBnG9sAPbu30jY8wL5zL8OOIFXRRCKbkOjx94Njpozj72Gis3Dcb62ZbtE6E4QqyRQca9a9ZUmvUtKqmI6DiIMZYRzovoDYkUSr/lMA3WcTWY5NUS9TM3XyFZXfbPREff73PviPt6nYvhJ/Ujk0cte9dzuJwjQHTjsPgn2d8OKk+P7Dbzfz3QcH6cvOjjqXdYeq7iBZBnP3b6RvaCu7Hv0Fc1csIpFJki/rLP7CP9CXPwC1qodxuLC7onJ2C+eB4yGOSDHDdd2b8JLQ6GPfivzbBd7f4nV7gdOe5Tm+IKM3n2uYYQIVUFVWmK4UGCtPk4klmZvteVbN6s8mDNsKKaeWYx/XPaiW35QfpfiqlRKp6bqgVpB8SaLYQEeRJbBs6B7dhbhqBbhuHf3ySnaAlyyCiyIL3kTpiyTFBYdOycMTg/68ludoz95/GkQqliCbqCeoti0wWBqn48rLGLztHoqveylZSydWKqJlO+je10jXbR8exDTn8Mm+PQDcXunG8VPtdqkZMXh1Ypgt669nZMEa1px5OpLpVUdt/3sIskz29DUUNjxF5V1vJDUximlDxZEwXIFUZL4UcOmSDCbsWEsFY1GUsC2T0dIUuVoJx3GaFpqKUfOVjj2/Wsu1W6KGgdCJg0ttBmJ8eqzIe9sHGSyfhmhZuIKAI8lMlW2qCe+9XpmaIG3A3+aXha+7b0d94e1MRfxsfQTViiVwJAnRtpAdB9et05tFXM5PeFXI/WoXy6xptKrOzU9VWDtfpTsj4HLohTXag5qJtRojTgPyvvMT/8DY9TcRy6TInr6WdR/8Y3qfXo+sextiW1GZ95XPsXTpV9jwm7vo+8CfovhImqXG6bnmSga+9h32fenrCO/7Grov8NUKgbejCWqynqBqmSzxUhHJcY/r+eP5CnvGeBA3P4m8bCHtqRh2zWDEipFcehZd63+JVa4gpxvR69kQVFVSWN7tddWMl3OYtvWM7DCOJEzbQrN0ilqFsl5tTFBt2y8yzb7GyaKEYVkNYlFQF0mq+IlANEkQBAHbsTEdi45Eht3lHNPVAiPFSWRRoifTge16CKqD61N8owjqc09H1/z+X8t2DquseiJeeDFammL7+D6SaoJzF65peC6wS5P89qiZIekafbs2kx0dwnFdhp8epOuMFci+N7oZSQja4gJdVW/u3zgpUbOb308VDj9WFUnGtM1ZkdCaqVEzdbKxJAWtgmHXFXUNyzhiv+SDudYI6h3bxljem2aiuo9CrQICjJcajwn2PmW9ypxsV4t3qUf3Xq83P1HMU2vvBF68TJ3vPuix58aKs+8fJks2rq5x5U/+jr4hDxxrP2kFV7/vdSiqQnFOP8OnrEa6Z0/D68YtlZj8/OQgzzaOz7N+AURbxRdy8Cmfgr9AJZQ4Ng7FWpkto3tDGfzfdbi+AqLtepPs8e5lGFC6gip5cnqCpQ/f1VAkCOiekig1IKh/eG6Gy7qKtOWG6Tp7BQ519ddW9Srbb2YMfFATgk2vpIMgYMYSLV7hRUmvIEkSSguLmSBWdi9iTrYt8lkCumlgveIlONUaWzd5k0vMH1+xSqPvmZbOEo9URoPKa6o4weD1N/H9j3+Fh39+O5bhHbPowCbSpQm2nvVqUjERyawnN0Fkzzqdyo7dVBxvYyhLoLkiplufHsx4AgHo86lK2qwUX9+OR6vg4IR/B+Epc/p9ZbYnstBqc+v59uL7oTZO2p/v2c7JaplXHnjQe09ZwbChWHOoOvXE8xK1UQ082rvbkap/ZuB/6yGofl+q4yGG77p4DgCr1ArtosWwFWNQzAKwfkeJnzxa4vM35fCsKj1EZbaIIqjZhDdGlnbXE5KF3XUEderuBxi7/ibWvfIi3vmFj3Dmt7/IsolBMuMjJArenGIrCoIosmDdybzuk3/GnCsuRfIFn+xYDFGRWfTBd1PZsZueHY+Fn9OquOBEKb6RBNX06b6S6xzX88fzFcWIn6BgW6i7thI77WQk00RHpODIjC48FWyb4hObml5/qB7UIIICpHmEvd9HG9PVImW9hjFDSRciPaiHEPeSRYmS0XxuAWWwZjZTKW3HCSmKiiQjiiKGbVHWq4xXckxXi1iOg+PPL5btiQFCRDn4Od7ketY2VkO/34k4fmKikkMzjZaU2QChn63w0r/58TA5tWy4a6fO/TvrBdDomjU3ZhETHAqOTM2V+LfbfRuRyL0UP6IE1Wsf002jJQVWswwsx0KRZGRJwrKdumCSU9dVOFwUWnigAvz08YNc+ZX72D9V4mBhjLnZ7hbzgcdwEASBlJps+T5AuE4BuGL9vI5eVOn4jyMtbv3y8TKnPfwz+oa2svRNr+esj32Ql/zTR1FULweRDB0cp6mYOWGrxJXjM9U7Ps/6+Q7XIVvxqKXVjm6gjqCKgsC8bA+D+VGKevl5W7hqpo7h9+8IPu31eK5MhQuGvxFK5qfC56YWrwA8lV7wqKbRBaI7LfHSvGfloFy0jpikhEJE0fnwYa0dgAdtz2TeQgQX5sg6quBiKwruLMmnaVvkqkX6Ml10JDItjwFPKOm0eXVBGssRaEukkU9aRnrNSey98S5c1/USVMdBqXrjbN+5l3rna9u0i/Ux9bZzk6xKVvjDn32Mjf91HYIo8NQdj/CDT32NjTffz/jWnViSwtCSM0iqQqhYa6n1zWDbWaeD6zKxc394TWxEeqV6pVbLtnu0XNl7/b5Jiw/9cJwbN9b7wiRBDJUzq6bmKfo2Wc64mE6dKmQ7doMPajREQWii9wqOzVO/upWffOrfufu717Ph5geY0m2myt57Vt3W7wWE/aedokFfwiVWKoDrNiCorp8QJCxvE7C8T+U9l8mc0+kds8VIU3FkLMfF8hfyYs1htOi0pCaZtkVR837DBgTVV9b9+lvW8ZrT5/Gxq+eTiTthgnrwv39AfG4fZ77C61ONlWeUqqmjnkESI9h25Pf1EPLeV76cWP9c+u78efg6rYXsfLQvalBTwu8R9KOKfn/t8Tp/PF8RLUp8eo2DW6uRPXU1AAVXBQTG+08CWSb/6BNNrz9UD2oQoiBiO3aLe+3YRFmvUjU0D6WdsZkK7+FZbGbAs8SptBA6C1CmilHDsMwGBDUbS2K5Dm3+XKr4/taGU++ls20byx+PVoNIkuALMz23Y1W3jHBdauXTeiJe2GE7XgLXKiwnUKduHtexcpFkbsp/D++xtGDxfw/Ui8lmZDjMk73PGLI8yuvBgovteFoGJaduZXe4OJyNYTAeFUkmJinULJ2Jcs5T1T8K4aGoS4AsNiaMpu1y46YKCSVONpaiOiO3z1VcFnbMYXn3gkMmm2q1vm+Y6UH/YmslGS4ema1mrFrg5Mevp7DmPC55yWrWLsySjvTly4YR0eRQGHBSbNIzVFz5BIL6YopkpYLkOhjJFGbcqxJFK9yeyEsXjuM+Z5uGw0XN9GhTQVX6ePdBNR0rRIOhXoEbW7WWqk8PkQyDquFw3cMSmw/Wf4+YLDBxy50kT1rBglPWko2nwhtZF+oJ5wYty6uGzuT77ioACqY3wc6XNRDAis9eEQyudVeyjQXtcw75XWKRapZlQyaWQhJE5r7ldZT2DvDAj28mPj5CMj+N4LqY8UQd8bQs2qU6Pfn8Ho0rrvtbhGKeqz/0Vt7yzx/kvG99nvhZ63jyxnvZfs9jTMw/CVuJk02IIVpoRZDg7GlrQJKYfnoH+XkLyS1azllLvARHEqHS1YMZ947viSSt+arDz9aXw41mYDNjWGbYmzbTcsZLWi3wkVSnhUhSEKIgNIldrdp4M1vuepRMVzvD2/ez/td386v3f4bh628GPGpyq5gjaQi4pAWL6/s38DfV+1jy6D3M2/IEsr9JMWNxKp1ev+zJw55QuelYLOmF0zq97z1ixdk4YuM4hMJZAGNFu2UBaMPBbWw4uI2iVmnqQQU4aW6Wr7zpDC5ZlQ5pisWntpB/5HEWX3sFouR725YLYSIaXkt/TARUdNG2w+9iRSjc8970WpI7nyJdGANaU3wFf6flAp++IY9l4yXhfl+VR/E94YN6tBFVbs4MeXT97MrFAFT8DhtLjaOefDL5Rx9ver3hzzkzmRTRqIuTHdskyXVdto7u5UBhLJKINW6MLcc+IgS10gJBDXpQoxYV4WskmZP6lrCgvQ/w0CPPaszE8BNUy7HrnotOvbgTeCk+15vcALGaaYFzIp77OBa/re3rJbQKb7y3XpuSfltRFPnLijbgIteq4LoUI0J0c0RvTj7oJ6imK4aK8wcsb109Eoov+CiqZbL+wJamAoxmGRh+gpqJpyhpZYYK4z7V98jn7qhyfXuyuWWgrPnWhYJIVW9MQoNC8eFCrdQTKzGyRxB85tSLZZVxXIeDufGWz83vgNecVZ9vl2x/AMXUOeXlF4aPpcuF8N+SoUcK1HH+qngaHxg/BWjccx5PcXye9fMcwaCotXWElEBxRiIa0B2P1BPyWMfMvh5BEEJV1OMxgg1SsAmJIkXBRl02DR7fp7FjpPG10vQExQ1P0Xv1y+hMtiEIQtiDOhLrDI8rOzIFR0H0F6UJPRBJchEgTNJmOz9ZlMnEZk9ig4hFjFAtBxJKjJiskn3Vy1nwZ29j631P8LPPfIu9H/prttzzOAcHR9F9uq1o23SIdXry0HW/orxtJ1e++/UsXL0EQRRoO+cMzvmfL3P5u19P+9xuyhdeydsuzJJQxRAtNCOCDlIyQebkVRQ2bGL05DMYX7GGP39ZB+X+BYiSyNiKNTiyggAkxebxHEifS4I35qcqhVA0aLpaCBFE8BI+T2HT8YsOsyeogiBSiSCo8UqOdfd9n96VS7j6Q2/nLf/6IV7x3S+QWXsS5W98DdnQGii+ABIOFyWm+em8jby3fZDFik/D8tfV7OgQuD6iLIpMLF2NKwi0VavgWJiWRy3vwNsUj1pq6BGbjlyL8YLTsge1ZnkUsulqYUaC2rjwG/6GyB6dYMfHPoPa282yqy+pf/divonm6YQIan0OChB3M1JM6b32KgBWbroVaE3xrXT1Yqkqm+Q5BDmV49SVjQOK74upsn0solir/2a13TsQU0lS3R3e30J9DEinnUFp83asUrnh9UFvViLvt4q02GQerf/wkUbZqIXVfdOxsB2rQXgFwDpMkQlAESXKevO4MW2HolYhXyth2haxGf2zUQRGEWVMx8SyPbTS9VV67TBBrfeyR61tnsswLNPvQW2+LifiuQvDMnl4/1Psmhh8Vu9j2hZVS4MW81orj+4gAvbW6KrT+J62GPCKla9Lj7L8wdvpGNjNcK5+388RvTVn2PKKhobrCQG5LhwwvXU4Lh7ZvOr5glcpaRVGipOsH9zCWMk7H900MHwxpGwsRVGrYvlCY0fjYR1NULOJ5gQ1KAYJgkBlRjvsAztrR5SkzoagCghwmFaZ36co1MqMl1sXH1Nxl+V99fl+6dZ7yXUv4pRF7eFj0eReMo16i4+qEq3tx08gqC+eyJS8AVXLdszaI+TRrn53UvcQqAq6jBYn2Ts91JCgBt5wxysCMhNtC5FANR6iPLJW4+B0cyVbfvR+AHqufln4WKDAWo3026X8hEPx16SRWn1xEgSwDpOgKpJ8RJL00X4A0/I2VDFZxXAsln78Lzjz7z9Cel4vA5t28MB1N3Pb3/0H//3uf0O3HATHpl3yvqPruAz96ibazz2ThWuWh+8ZJOxLzz2NP/z79/GeT72Gl57sJSzhdYt8l8lKHk5eRmnTZqxyPZkcX7OOXZdcjZHOhuM8KcyeoMqSDIJA1dTob+vFdjyFyw1D2+vn5lPvPCl577+zWauIgkAlUok+897vIZs6F77xSgRB4GktzYGTzmHZ33wEpqc45fHrmyqvXZLJ+9q9jcybMyNIgnfETPKRrXpjyJXluk+d42DYJrbj0Ob4iL0do+wnwdEEdbTQGkGFgMJos/FAPnwsQFDr19DAKBbZ8fY/Rx8ZY9XnP00q4pcbUMqiESCnQYKqaFUky8KR5VAECyDePxfj/EtZ+8jPmb9nfVNPL4CjKOx+yZV8S/fo8h+dWM1np5eFPaii44SFhRNx6LAdl3t3TnBgutqAoJZ37SCxfAlx/xrWxPrmz11zOtg2hQ2Nfah6KosjSai1KvFinuX330r33u0Nx0iiR/E91iieZXtUQq+HzcJ07AYF0XqRafZ7GLx5oaa3mjcchgrjTFULdCTbDvkeAcU3+I6aaWA6VjiPeOwa7/WSb6n2XLOFPB9aE9v15gnjMP7VJ+LYxHBxgrJeY+gIqZGtwvHVlwO2z0ymW6B50VR4cd1wLq52dFNxvXs4I1r8RYfnedy7e2s4x2biImnTS1ADiq/lrz4uMOw/FqX4Tg3n6d21uaUfekcyy0QlR8WssXvqANPVItvG9wMei8vy9yGqrIDg0+Ad+6gsBqNiZu0tElTLcVFE2WM4zUBQH9+n86mfT1KsebTivu1PkRk92PgGrkt6qo4aRsEdQQDnRaTia9hmQ+tPNFTZIabAP7y2i7bJQfqGtrL3lEvDNiuoI82OJCG4Lh0HPbtAW4k1eKaeQFBfRJEueQiq1tYZbg5n8ui9TcOxr2rPFpZj8+jAZjaP7mEgN8JUOY9mGmFVWuB3Q3t6rsKwrdAyB4hUimJe76Do9VfOrERettph+me/JH3KapJLFoWPBwiqklAZs72Ebrvho0U+dedgRQwnAA9BnR0dNX1xgiMx9VYlMex9tV3oTLSFGzCA9Nv+iOU//wFXXf/fvPFfP0zurJey6uFf8MRv70WvaLTd+Qt+/umv890P/DO1oVEWvPHahvcPElTHp4cKkTEY7bcMYrQ4SeqKi3BMkx0f/0y9V0UQIiidjxpKzeMnWIxFQWBF90KWdc9HkWTfJqJRPTpAwoNE9VCbUlEQKfkJaqI0xfItdzG07uW0z+lm2Irx3rE1fH+DQduZp1NZdyFrH/0F2fJkw3v0SQZz5XqfUUZsvYm3IoiyK3pWQ4Kvzmm5Dhnbe48RK0bZ8a5FKvJeowULZigQmraFbdtopsHtW6fYN+kl/7IocOr8ulAWeOO7+L1fYIyOs/a7/0HnS84LfyuoC4C1iqBvNl7KA6An043N1YD7oU+Q61nES276CvpUvvUbiSKTZe/cH9XauaXSE1otia57VFX4F3N8/e7dvON/HuPSL94TKtXKAuS2biO2fDGqv1YYkQTVXLkGQZEpzOxDFUWv/xvo2r8T2dBJTY41HCIJUug1eizD8BNCb+PrbeINy+TJIU990+t5s1EkqaUAS6xc9GhnotTSl9qwHYq6pwzcnmi2NoqGLHlKwKZj0ZbIsH96mHQsiSRKOI7bgHbVi8PPvUhSkNgYlsVDA0+xe/LAc/qZJ8KznKuarXtHjzQCBWbwCi0zqeshY2tGD6pTLHLX13/ETz79TQZ+eVOoeRBdV4L1U8VhUadIouipvx80gzXGu1ccB0Zsr5AYTVBXbnyAjoE99Oxu9sRsT2SY394X+h6XdU9xt2bq6JaJC+F9EPSregjqkSd9UQS1rUWCWtZdRvKib8XTfN/XTJe7t9VITY3TcXBfaJMXRHpylFgENYzuT4J96ovFB9WwTWqz+LyrskMqlqArLXHyEzdgSQqFdZcwE9O31Bi5+UsAyEyM+o81IqgnelBfLGHoxLUqjiCipbPh5rCJ4itIOM9BX1CrMG2LsdIUBa3MVCUfmqrrtknCN0sOzct9lPV4i6gAAEQovrGYr67rJY8JI2olInDe1GNU9+xjwZ+9reH9AkGleCrGu0bX8oHxk3lK99RZg57K8bJD0U9GEA5P8T3SBFUQBOIRmm9CSSGLYtMGc3fPMq4tXM71l3+IHadewdO3PMANX/gfrHtuJdnuiYd0nn4K8y4+r+F1QTIZIIHRsRl6fvoJWTAWll54Mcn3/hGTt97F/n//z6YxEoi1pOXmTV+0UhdsVINNs4d819VfLZ/i6xJsKg+VoAohNfCkJ29CcBzK570c8JTpAJ4c8MbB/lf9GYJjU/jNLxvg0V5ZDyf0siOR9TcSM5dVK1ZHHAPBIMGxcXBxbIuk73U4bsWo+JuSRXINCe/8xoueSmJ0I2DYpt+3Z7B5qC5y9OZzFjK3rT6WTNtC12poN95N18suoW2d58yl1Jrl/mvtnZS7+5hYujp8LCiSxYte4ayVj2k8neD+V36ERLVA7O66Y1iUVaGZDqP5GSI4fgFBcpzfCSr1+xD/dvtOoK4GDtBrldCnp4ktW4zqCx7pETuqccMktfZk8o+06EP1UeyUjzrIRmPfXFAMNY+x3oFhez2WNVMP79nxco7pSsEXTDJDxGZmKNUKSx65m6WP3EVcVinrzeugbtpUfYGkQ3lNAsiCRM1PSvrbeljc1c/89j5E33s52gcbCAI+12uvd39bxGQV3TbRTYODhdb9ZCfi2IVhG1T02lEJ/8wMy6esB/+eyT6wHI8RE12fSk9vZf2r3sLeDduwXZddn/4cyvXfx3Xd0CcdwEag38rxn6Wf8vGd32fbb+9mwxO72VVpvk/GLG/c1xNUlzbRWzNjs1A/47IaMhlKfoI6mBtlulYgE6+rwoesA8ej+D4TkaRWFN+BSfjyLRo3bKxQbZGgAkyU6noIAB2De1j82L2IpkGikGs4thFBFV5UWgembVOdxee9NxOnL92FMDrEiqduZ8+ay+nJNtscWvE4E8tPbtjUWGoMswFBnV3E7oUcR2aMdCLqkfcQmnIiAaIY6f9qnOAC4Qrzd4Cgbh3bS65aRDMNz0dKcrFcm5P7loYJg+ArwAW0rbhy+ETqhRKG5dGnBN/0XbAsRNvGFcUwGTMTSeRqmYH9ecDr8br8ZMh/+mfEF/TTc9VLG94zoPgqCZWCI7FJr0/Eut+jl684FJBpE60j6kFVJaWpj2q2iCtiSKWxbRFRkJr6gx/bq2E6Agjw8JXv5zJpiOEntzDv0ou48vWXUBibQLvwYoSZQg/+bx4kqIL/voJtI5kmriiEFFDLsVFEGUWWSb3pVaSHcwx+7TsobVnm//EfhW8ZjPPUIXpQoyGKnpJmcF1sx0GR6hRfx3EQBGZV8PW+hkBFd5BMnVUbb2Zwxbm093QA00zajeN3LDWH2oVv5qx7/4/PbHgZ61b28arUOEuVepJXdOQ6LXcG4mOpUQS18bopuoboukw4CgZiSPGNiS6f693BX42vpmp4nrbRjYBHAfTut6lIs85ZizsaPrtqaEw+9AjudIG+17zCe9BxUGt+P2kiGSarZizO8NqzG14foJzJnDc3RW1igogrIrneJYz1n0Tbg7dgWH+GAAzkh7AdmxU9i/j5+jIzBX6rlnedRNfx+6ZeHBuHYx3zRjw0JL52dYigmlJ9DFd0E2ftcqrfvx6rVEbO1H/DAN0PNnKyoXsNbGExSERz7GOekHnj18b02SbpWJLx8jRpNUHV0NAt0xNlEZu3EYmCR4OUDANZkmkh4kvFMNB979bD2Usk1TjZRJqEEkMUxLDwCoTfOyyOiWJDUey5iqAHtTOVRjN1TMskdhytq8dreGih4RdlrGfk/RuIIAEtLZoCBDUhxrGKJfZ98euM/fpm1GyaV/3l22k78zTuuWMDB//nhzym5uh51bXsf3IbAxu34YoSVzyxhftmjL9XdD3ETW/9PEY8zcNaO8uUKlv0DA4g4yLhNIgQziYVpMoqumVQqJWomRoiApOVPNOVIos654XHBQmqZVueR/kz6EFtRfEN4pePl0more/bYs0JfekB+nZuBrwiW8h+UxQk02xMUAlEkl4c64xpN/tDBzGnLYUkiuz9l6/gShIbL3wzL5W8pL/iSqT8diszngRBwEikUSolbBf2abHwCkpisxrz8RInENSjDX/hLSc8xM6ZBUENpP9/Fz2ouVrJ63OzTXTfm02VlCbaVcyvvFUiKOPxEJqlY9hGC/Q0Hm7SamoCy4a5EX6+sPVJtM07WPCutyHMsIcJKL5Oiw2F5idcVcOhYAcU6eYeVNd1KWplnyJ05AgqQDxS0bJdAVlqXkAKtfrYcUWJk9/yei79k9fy0msvAKBzbg9KTGlAVKYXLgv/PVPAK6hcWrFEeN0M2wyvqyiKLPuXT5E98zRGrvtlQzIS9qCKDl2SwU/mPckbM54aVasEtU479EWRfL/CoLfHwZ1VJTG8Lo5DSbNYuvVe4rUiW8+6Nuy/GLMjiKfrkqs6bD77D8h1L2LuTd9n2vS++0q13lObEu0QQZ0ZjRTfOoKqmbpHrxUEpvyxUHJkntSzCAKcEy/wsqQ/J+hiA43e8KmRtuuQr9R/y550YxW0ampM3nYPQjJB16WeQp9aqyI4DmY8gZbO1q9Ji/E6U9232t7ddExc8X7vPadcRnz0AH/7lSf4q+smKFS9325oWueurc2IbdGvkJ/oQX120TGwCTERR125FCXwAY78liIxei84DxyHwvonKetVT+2axrEJXuEk2p9WV/F95mtN1dCYqhQaHjP8/tNgvVjUMZdsPI1um+RqRQ7kRz17lxYIqhSxxREsC1VMNR1T1jU00ziivn1BEOhv66Uz2TbjGbfJ4kUUhOeE8hyNoB9WFL1kWbP0425dPR7DdV0qRg3dZ6fktWb7rSOJYB0CT2DLsJoRVNtxEC2bjW95DyM//RWdl13IBV/9R+atWISdSLL0Ex/i4HnXsPXux7j/45/m7v/+BQNP7WTf+qdpO+ccrnj/H/GKv3gLb/vch9n3jk+QzQ9z7p3fBuDjE6v4w+EzMBBDAcS44LAm5osHCRCrNgqmBSEKAgs65jBdLYbjXLcMLNduKJArolxXmD4K4aHDUXyj0YriCzCUM1G05vVEMo1wvxK0TDVQfAXhWSHjx1uYttWAWEcjmxCZvO1upu64l4lr3kY10808f//ztF63Miz29XvvFU9gOh51/D/X18fzcQqeAicS1KOPvNeYHySo7uF6UH9HNjNFrYphmeiWju4ruc2MmKKimwZV89ALaVmv8ujgZibKuUMe97uKmmmgWxYx/zuZg4P85kv/xy8/9e+hqMiIr5AXTVATd9yGlM3Q99prmt5T8hFUW1GQZtwFAYJaNVzyTkCXFRtQNvAKAwfz4+yZOoCIQExWWtLdWkU0QbVsDxk+MGXzqydKjBe9yeXg1IyqrqSyZN3JyGr9txVtO0TXJpeuYnzlmvC5aKKF4zBvi0cfLHfXbXCCYgZ4CaqLy5w/uIbqnv2Ut9TFWIIkKCXa/FFmmLmSzp+3e6IQrUR3Akq5aXt+csFmwHIsbDxFWNs5tD2FbhkUqxanPP5rpnsWM7pgLXP83zf4vQFKmkux5uBKMk+d/waUkUFqD9+P67oskDWKE9NUi2XSokXGqvD0HQ9zYMvuhs+yIqJCruD1HjuOxb6pYRJ+Upb3E1QXgb8YP5mNc05BAN7ZdpCXJScpa0JD75vuUwChsdjQk2lMUCt6jcIDj5E653Tm7d1G194dqFVv42Wk0piJeu9zVPwoPF+pPpby8xZS6+hqOiZIUIeWrAOgY88mCjWXR3fFwZH4/kNlnBZ7grLhggCC64Jz/PooP9/RsX8LqVNPxpUlFH8zHC2O2Y7EvPPPQ0jEGb71DgamR9if8wpAMxNUaKT5SuIz70G1HJv908M8dmALm4Z3NiRZhu0xAERRYnHnPARBIKnE0EyD/bkRCrWy34PaguJbqxeGFF1DEJqT0LFSgZqlE1Oax/TRxEx6ZkDxfa6Kw67rsm1sX6gqH5dVqobmfZcW6+6JOHZh+AV4xx/vW0f3MlaaPur3MX17IADLaaaDB/Ttse/8iMq2nZz3Nx/gzL//CNkOr1hoq3EEQeCRy9/F6VdfRN/S+Vz4lmt4xxf/ktf+7Xt57VtfRv9JS+lfvYRkW5qXvv9aRi68lqVb7iFVGAcEbJ+TGSSoquCwIKKXIBkG4izaA23xNEu6+pElOUSSFd/zPny9KHpFplCB/ciSviii15Z8ZoyAqbKDW6o0Pa7oWoigBuvaTIrv8SzmebRhOha1WRLUlF1j12e+QGr1Ci786DtY06+yrstCEODBWgcFR+ZgvItSr4eaG/FECLoPR/ZHinR8oqdwIkE9+vAlxkshgtqa4isKoqei5trP6aYuULctG1UM26Sia1T0WkvaSzxEUA8tMLB3aohCrcyWsb3P1WkfVWiWjumYKJLC5J338fBb38/UgTFq+RJb3vdRtOFR9te8iTRIYFStjPTQQ8z5g1ciJZo3eAEC4cgqCaXxBh7KWQxMmh6C6ieohppoooWW9ApdyTZMyyKmqCSU5s+ZLaJN67Yj4DoCP3hA5tcbKnz9zjwAgzMUiWtuPRHZayZAgI6De+ka8JIta0by4kSoqtnxYWRdR09lGFtxSniMYUUQVDyKavdVl3uCOXfcW3+voM9RdEjMoPm2QlCDhVKzDGzXbaBT2bbnX+i4Tmjp0yoEQcDdvoWOyQG2nnktCAJ9PgUq6N0BODhdR5NyZ1yMePIaYjdex5a7HsXdtY1f/fN/8tO/+Xfu+uZ15D/zcR6//k5u/uqP+dk/fIuRXZ7CrxO5X7zE3sU0dGzXpl9NIwA5J1IYECC5sA9BgIWyxt917SZb8goFRd8827CssC+wUKtfo5kJ6ti2LVgjY/ScfybtQwP07N1O3Bdi01PZUEkXWicrUQS12tGMngLE/DFebuujlO1l7sBTAOwZh3+5QWHnaH2spWL1cV423HAcubb9otk4HMuQ9SrJob3ETzsZx3VQgrknUmiyHYmezl4SF51D7o77aFeTaKaO67oNgmb194wkqIL0jFV8B6ZH2D15ANu2qZlaKL4CXoHFdCwWd84l7ff4x5UYut+PPVnJe/OyKJMZGyI1ORq+Vq3WN6eyXqOiNY8bzbQo1spkY83o6pGGC03quaIQ2Mw8N+vuZCXPUGGcmqljOTZxJUZ7IhPOaSfi2IdhmWwf309BK4dtU7ZjU9Kr7M8NH/X7mbYd2qXM7N92XZeqoaFNTTP2v9cx75LzOHVuhkVPPEj70H7A0ywwLJeSLbH2lZdy1QfeysrzT0dSFdrn1OdgAZhetIwFnQqv+6c/QQBWPHV7w7m0Z1QPMRUceuXGdh11FhQ1CFmUvB5apzXVPgAjHNyjoPjWjzscgnqoMIoVbNfFsF0sv/opGxqyP8e0RFABfGXuF0MYthkCIjPD/NXPMMbGWfmPn2RBb4K/ekUnqzImggC7jSSvGVrHbzvPqLPhIr9/dK9yAkF9kYTruuBXfw5H8YW6muBziaIGFUXdMry+DNdBtw06k9mmY2N+70JFPzwVKVCHeyFERfeENOxd+9j2wU+Q6O7k1R97J5d+4W9wNJ2tf/4xdvhF1G4/genf+wRYFj2vvKLle0YR1LOWNG/6//HXU1R0N0TN7ESL/lMXEmqctniamCQ39EUdLhoRVJiugO73+w1MWtQMh2JthhG3W79d95tJBEDR6sWGmQlqgKx179vJPF9JrzBvAUSSQsM2w2JG0KeitLeRPW0NuXsfCo8LRJIS2A2Txhd7tiHqsxc8NNPw0VKvUGPYQUXX+7/sCqiziEEsbJ9D25MPY0sy+1e/BKgXIEYjFcKBCNLcllHp/Po3Ka8+k/W/uoPbvv4jkm1p5q1ewsEtu1m67iSueP+bOfmSs6gUK9z89R9zcOte9AjN0PGvj2UaSKJE0k/KqhHfylVzVcS2Os0GQNZNHFy2je9jw+Akd26b5I4tFnvGpNB7VJGEpkX/wO13AjDv7DPCx9ITHnqmp9IU5synMG8Bk0tXUeib33SdnAiCOpsVUliEEQRGFp3K3MGnwHWYKjeOsVVzFU5dUL+2Fd0NkXj8ueZEHF30Dm9HcB2kU1f6Cap/DdX6mDNtkZSapO3lF+MWSgjb9qHKiicO16IoIUWKjIHNzDPpQS0bVSYqeUp6xbPbcOpUfK+v0vN3DiImq9T8DWa+VqJqaMRtm/6nH2fBxkc9fhmNAl+yrjHZwhsxX6tgOvaz1kMw/O/dNjTA4kfvIWaZ2DhY7nOz7o6WppiqFBgpTpL1RWl6M10hK+REPLNwXZcv3LqdV/7H/dyzo1FsasvYXoby42wd21envjs2uVrrteNwEfSYqrLSdO/UTB3NMqj9+AbsmsZpb3xF+FxQeLHUuC9uIzBuNY7fIN24+MC5bFx7EePLTgYgPm8O7prTWLL9/tDPOKEKuLIELrwhM8orU751juvN17LRGkENwktQ7QYBySCy8TSGbRFXYkcskuS6bgOCuqa/eR/ZKjpTjeNewCVl1rBtwCPf4Lou8hEgqF4P6osjrFkovpKpkfvhj+m6/CKyZ6wNHw+YKSNWDBsRw64Xk+0GoKD+uCofvwjqCZGkowhBEOCVb+Px3U9g2t7EMRuCCo1WMyrPDfUnEGIB6Mt2t0xMg4jLMTRTp+hvRuQWJtSAbwug0Z7IHPK430UYlsl4OUehXKT6mX9DbstwyWc+RGdpCnPlMlb9y9+y9YN/Tf7mG+GaRXRJXuK5YPdjSB0dZE87pek9JUNHtC0cScKRZN5wTobtIwajhfpEGYjF5P1KlNUiQdVtg5ikkI2n0G3jqBLUKIJq2TTZrUxXmictzakfM2Q1f5aWbRTfCRKLRKFOgSrMWdD4GsugK9WOLIghggrQeckF7P/KtyiPjZLumxMWYuKCjRRZPs6JF2jP7QYahXsAOpNtTFcLIbJgWBaW7X0v13UxHZsVQ4PMHzmIKwo4kky+fxETy73fLKHEaN/4CMOLTseMJRFw6wlqpAd1cKqOoHSkJNIJmT3Xvpc/SH+F4kSOl73njcTTKQpjk7TN6UYUBTqueimdiXaeeOcHuPE/fkj2gac57fvfRIzFwutmmTqxdArJ8DbbyxZmWCEp9HfIvOoMz8olOvWLusdm2DFS4fM3PRqhzNbHTmfKG09Pj+wmocRY3DmPsbvuQ1o8n86uNvD3ZXHfa9lMpHAUlZGT1zVd3yCiCOpsVkjxCEtgZNFprHz6DrrG9jI1Z3nDca87K8Nje+vJT1lzcEXJ68E2DSqHaQ94sUerTWDfwa0gSQirl4Flouo6riDgxBOAN3YNCxKKSvu5ZzEiiWiPPklqzTKqpkY8kcUVBATXxYwnULRaE8XXcmxMy1PrbGX5MltYtk3N0CjWyvSk2zFti8HcKHunDlIzdVRZaegTVyQZB8cTCHIs+jJddEbQ3FilhJ7OhgJfAIpeY6LYnGTrls2SrnlNjx9VuC6mbxEyd9tGAOYM7GFXZ9tzQvENFPKLeoW+TCdtcU/MSvQ31gFj6lD2WSeiddy/a5Kv370HgL/79Rbu/WhPOJYLWpmSXqE9mQ2LZDVTp6LXQhGvo4mgBzUmq2E/se047Jzw2lbKo6PUfn4zva+6kt6OFBTzDa+31BhVw7vXb6z08mdtnr2Q62dX47YKCAhdHQ0FYfnSy2n/6pfoGtvD1JzldCSlcH59Q6bOQBiTM8xzSkgzBRBnhIcABwlq4x5TkWRO6luK4zrsmTxwROi+HlHJUyWR1XOyzGuLM1w4NOvuPZen+OXjFooksGfMpMutEaPx81w8pflA4NIKHCZmiiTN4if++xau6zJW1Lnt6eYC3dI9j2AXS/T/8VvCx0TLRDJNNEFi2t+XBo4TAPu7FpE9sI9fl/sa3usEgvoiCztCBww2h7KuMXfLE2EFGQKrmWOvrhgNwzdnbk9kDpmcgpcwx5QYVaNGoTY7dSTozzhStPW5jPFyjlytiPvgBipbd7Lskx8mq3p3nBlP0POKl9F52Uvovfd6LMOkWzKQjRoL9jxG+6UvQZCa785ALEjLtoMgkIqJ/MsbWlMjH6x1sMXKUpi7sOFx13UxLAtVlknHksTk2BELJEEjgqpZNo7TeCsGfajR0CMU32Er3pAcDZ55YRN65kQKC64osuOya7AjaIzjOhimQUJWycbTobgIQOx8D83bfeut3rH+OFexyUqN55Y1W6Pt89p66Ehm/XvAF3JwfHqjv8ntH/EWdsFxkUyTtuG6j+BN128iUxhjYOX5AHSKJgouBUdGi1yLAxEEtSMpkoqJ5NQ2LnnnH/Cqj/4JiWwaQRRon+tteAQBphYtR1q8mDN++X2W/vVfUNzwFPv//T/DayUIAq5jMy/bEyYD8+ak+Jtru3jnRW10pb3Pf7Cn3vOrmCa3Pl3hX2+stOznBEiqDjVTZ6w0xcH8GPnpSQrrnyRxwZmoWvO9Fu0/nTUiCUkUbYvK9UeNukcWngoQ0nyD+PwfdrNyjtpA8a3ojj+OBGzToGZoL4rNw9GG67r85U83cfLf3dr03NzhrSRXL8eOK6SrFcDFSGVQY/XCgm65xJUY8c4OlJNXkH/oMVJq0rOREASMVBpXFCn3eP3jcoS1IPrq5mYLu4zDnXPV1DyU1vFUTYtamV0TgwwVJqgaGkm1RXuEIIY09p50B7FyXVwpVi4g61qogA0g1mpMV5qTxZSaJqUmKGsO/3Fbjo/9ZILbN1eYboG2zhZtiQymbTXaa4SsjWM/TgtamYpRI66oXmEvUhz6XakH/77GV+/aFf57cLrKwFTjulLUffTSLzyUjSq263ho52ESuZlhOp6/tSopOD6COlKcZLgwwVh5monf3oarGyx6z9uJlRrFwxBAT2eo+hZo15f7mLBVntYz4bw/YsWQRYjNQK8yV7wcQ01wyvpfAdCREkPV+GiMSF7hQzoCBNXzKzZb9oJLougVT44QQdUjaF7cXzN+9GfnsaR7dhp+Kiawak4bn7imi7+6upOLVydCccJHtHb+aWoZbx85Fdet+3nbilrXb/H3x4n8FAtHDuI6Lw6RpH+5eRsf+fFk8xOuy6qn7yA2bw7t59YL0wErpSDGCRDSaII6LSa4Zugsvppf1PB2ynGMoJ5IUJ9lRAVK2kYO0r1/Z/i3IskYthVSop6L0PzNhdyi/wAgMz7MkkfuYo5fXU6pCSqGRkGbPUE1LE8gQLeMZ22I/WxDszxJ+eqvbiO+oJ8z+rOhH2CQkM35k7cRq5XY/PBTKLicvOMeVKPG3Ndf2/R+qckx5m96FIBaWx1xnA11GLLifKa6lmpnT8PjnvqtRFyOkY2nyMQSYTX9SCIeSRh008GakaBG0dzF3X5yGDHzLjjyrIlJENGxWW3vbPgboGLUiMkqKTWBIsmIghguDPn+TuTODmoPb/AOFkVcUUTCpU9q3AzIhyjASIIYbhZ1u26O7jguum00+ZFKphHSn6ZuuwdHEDmw/FwA3rba+5whK86FK+rf92Cu/vntSYlUTKDkHJocEqjhKp3tLHjX2+i99mqGfvAzzOm8X9EWWNjWS1yJ1WXxWwgUTfYu4D9y3oIQtyxu3HjoBCGbqFOyTNtm+5234ZommQvOalY9FMBs0X84M6KKrkG13nFd9k0PsXNiANtxcF2DjpT3XC3TRb5zPnMHN4UvO30R9GZ9r9tYfSx6CKr3d0wU0S3zqDeDL4bYMVbiFxsONlkGiLZJz9AO0mesxXYdUn5PmZZta0C1NcMlLquokkzm/LMoPbWVhG5T0avYjsPBU89l4KyLqPksiZljRZFk33P3yNEkzTI8azJBYG62G9txGK/kyNdK5GpFClqpJStEEASKWh0hzR2YxnY8Y4h4qdggkGS7Lk/vLLQs2LiuN998+dYcGwZ0xos2P3y4xMd+OsHUESapfZkuFnTMYUG6LgwmWWbYVnAsN7pVQ2Pz6B7KepW02lw4CgReTiSoRx+247JhMN/w2P27J/3nPFuyoFhu2hZdqfYQpX5GCWqIoCpYvh2gaZvhfid/2z3EVy6lY24vruNg2G6YDOw5/2VY8WRYSCk5Mm8YPoMPjJ/MdwueourX84tIx8WmfcXcee3sPPUKlmy7n1itSHvSsyqcWUef8lk30mH2ju2JDNO1IgWtMiuD62jGZXT+Coroi7tT3P1Xl/Kvr1/Y8jXd6caTv3hVklV+grrdSHFbtYcBK4HteHoVAdW3zj70zmvR4w+w7OAA2WL+995mZryk8e379rV8bvWTN9KzdyP9b38TQpS94s+rJbm+J4jqf2im6xfuG8ecegJBffGGO4PKk/BFlABisuJv6J67JC/oQVVaIIW4LnO3PkmsXKJ9aAC1UiaueH2o2iEmdMPvzwglyp/HMCyT2oFhqo9vYu4bXk1matyjh9ouP93ib0BOOY2RhWvZ9Os72P3YU6y574fkuhfSec7pTe8XLSDUZlBiZ4t4C3Z2Sa+SUhKkY0lOm7eScxeubYk2zP6ejQiqZTdOKmOF+nWf0+b3f0bEiWpO4+9tt1icogiqlm1veM6wTQanR8kmUmTint+WKAo+FdcEAbouPh/z4Y3okx5F2JE8KtJSpRHpSzqzL6JBH7Yn5V/vYQzQ25mTqeC6SKZB8cmnmfvQDYzNPxkt1c68dolXpCeRJcisWMDCrtaU+Y6USFwRqLizz8p3d65pshda8J534FRrjP3m5vCelvzNbSDqYKnNCHkqJoaCBDHbwj7Murq8T8H0LRIM22DvnXciKAptZ56OWmtMOiw13kAPaxVlvYreonI+WckjCxKqpDBUGGf35AHedH79uJHFp9F3YAuin9CctaQ+trKJ+mcWNQdXCmwQJI9VccJOoyl2jLa2u+gc24to6iTO8JD2dKWCAGjpxgS1ZjrElRiqpNBx3lngujibd5JUEpT1KmYyhZZtDwWzoiJE4CEppu9xfaioGhrbxvZRMWqU9SqapXtFGJ8qCF5PZ1yJIUsKbfFM03vMy3ZTNTXmZLrYOqRDLo/teEWneClf9++NxbFtSNH6nEqay/89UGTPeOPzlg0P7DyyMSYKAm3xNPEIohyrlBvaa45VDOZHyVeLFLRyKBoVDclXDz7BMDj6mKro2DOqGOv3eetOxaii+9oFlu0JAqXUBCt6FtLuI+i6ZRxVMcK0TSzbRpVUbNvGsi1c/P7TsXG0p7bRedXlqNUylg37jAQbtQw39J6NmfTuwfFSfWw5CDgI/E9hPlcdPJvtRrqh0BdEX5vMwtdcgug6zNu/kXOWJrzCr8/sCaLk+sy8wyTecSXGyp5FLO9ZMHuCiuDZnx1B0qe1SFCDmN/Rei3KxP3HXZf2of0sUapc2uud9w7Du1YuArdVPZaaacNOsTNMUAXHRorqWLi//2J8B6Zbz2/dwzs4587v4Jx1PvP/5I8angv2BxWlPvdEHRRqRutrdkLF98UcgsDU4uXU/AQgKlqjSgqGZVLSq88ZZUGzjJZS/xXdQdI1xIi/V9vIgJcwuM6sim6u39MT+ID9LnxcDxW6bVK86wEA+i/zqJ6W44Fsv9xs8sffGeOh3Rr3XvNXyJks93/vN0i2xT3XfrwZFXXdUJDHUtUmVHS2UOUZvRSuS65apCOZZU6mC0WSjyo5BYjLkeTRdHBmJJwjkQR1brtv8SLUf4uqK4apnSsKoYhRw3lGxXNmnF/N0MnEk/SkO1nQ3ocoiAi++mXZ8BCC+X/2dlxdZ/dnPld/YQukOe3ojSheJETRQ1Atx2nol9Ysg4RlUi2WObh9H5Zh4voblNq2HTz9rr/AiKV4+Ir3A/Cpa9rJTI15dKUlC1neN1uCKiEIArKqYLjN5zpkxZr6cAHSq5aTXL6EAzfdSslXKQ3UBQ+FoCZVgWlfSKtDPHRy0J6Eq9bEqZoatmOjWyYTDzyMunYViUwGeQYqJlqHLg6V9SoD0yM8IdlMLFvN/rMvDp+r6FW6Um0k5BhFzVNKTcWn+eSrTeZ3SowsPA3F1Oge8Wh1PW2zJKhVJyx0JESJmqk3oGcnwos9460ZKXMOeAb1sdNWk4mn6HEBBPR0lgjDl6rh9fqLokjfWWcixWJU1m8iE0tSNurjwvA3x2qtEjINoC6WcjgEdSA3wv7pIdYf2BqKHCWVePh6ANMy6Ul3sLBjTkuf4mw8zerexXSl2rnhyRILFG/Nsx2vfSJW8ZL1YqodgLaI93Ck9Z6nDujcs715o3Z2PM+7cg8Sj/TOHy6iPa+yrqE4zjFHM2umTq5WIh1Lzkp9DuxPTsTRxXixOREbmPbG/VhpmpI/5wRFTtXf7yiSgmlbTFcLPLBvI4O50ab3iUZRq/D4ga1UDR0EPJEk3w5NtwxM22LizvsA6Hn5ZWEh6FGtnQ+Mn8LDxTrVdbzY6ncWqPrF0VS8ef0xbJNTLl+MkElzWe1RTlsYw0j6zCtR5K5qF5+aXEnB8Yqhh6P4glekaWUrGJ6RIHgtK0dQPIkiqIkZCaogWrzuHJ2zlqhIuHyuZzt/0nYg1OvIjA0xZ9smlj56N3N8ltUBs472/dPUci4+cC5/N7mCv9q/kJGSN3+JtkV2bKj+OS8Ciu9oi57eWK3IS3/zr8T6unnJt/6pAT2FOsW3qtavaVQBeDa7mhM9qC/ymFh+CgfWXQB4kvrBxiEmqxi2wVQlz+bRPc/JZ+um4fcf1Ceo324s8/7vjfOLu0Yajo0XC2E/wmyJp+Enp8ALYrE1LIPKXQ+SPGkFHe3eRO668M/TywjQt189UaaW6aLjQx/j5e97E7kP/Sv5nkVN76XUqkiWha2q7L7oqgZrkUNFLHKYaVuMlaaRRInOZJau1Ezj+COLKMVXM21SamP/8FiE4tvXFiQI9QkoL9Q3SLastkwco+j+zORKt01iksqCtj5SagJZlEI6blmvkY4lSa9aTvodr2Py5jvJP/I4kmk2UXKDmLN9U8skNdi01Sy/182yeGhnnJ8+6mI+tpUf/c1XufErP+C/P/iv/OAT/86DP72Vx976/0CSuPUN/0ChewGSAB1GGcFx0FNprHiCJd1KQ69kEO1J7zsnVQFVqE/eH5tYxVYjzd9MrqIn03rGTlx6HsamrZTyXs+R4EkPsu2me/nFP/8Xe7/3s6bXJGMiOT9B7ZQOnRyctsjFxqakVbEcm+rkJOVtO1HPXIMqyg3WIQDiYXrXi3qFTCyJ7TpMLVmFFqGsG7ZH+48rKqIg0p7IkFDi2K7Fn1yUYWThWlwE5g5sIqEKOG40Qa1fn0LNCXukUrJKUa8wUc793m8gjjZ2T7ROUE/e/xDxVcsw21Ke2rdfdLDUGFKk8FXRvet/6twVrF10EgvOP5/JRx4jHfP7UP2wFRVHlhEtq4H+J4sylmMdNkHVLIOxco6qXmOoOEHFqJFU440I6iw+2tGQfc/FrK0h4zJuq+wzE56l1ai32cwl2gHoiNwXa+YfXkjuSz3babdr9OzZdthjg1BmsA8SpoHjOjw9smuWVxx9eAmMSbefeM+MwPv5+S7qHo8xUW5OUA9Me/PkcHGC6WqBhBLnYGEMINR7UCQZ0zaZqOSpGhp7p4ea3icauycHmSjn/CJsot6/bds8MZBj+7DF5B33Is7toW31SlRfq+Og5a23j+3VQqrvRKl1US+IEFmMxM7xAWq2Sfric3HveZD8+ieZWLqa/WdfxHWLLufTUyu4r9ZJwUdQD0fxPdLwxIc4LDLZiKBGrfAcDNtgaZ/F+1/awWmxIufH87wzO0Sn3zqS9luvcEH1VcYn7ZmsI4F7al2M2zGG/AQ1Vi7Rt3Nz/QjHQ1BN22Lj0A4O5sf5fYuRwozCnOtw8W+/RLKa59RvfB6lvXlfGVB8tdjRIajqcSyFeyJBPUbhyIq3cbDtcKMeUHzHStNMVfLPyaauTvGtj8Kfr/cmVStfwnFdjJTfcG+Zh/WI2zVxIExKjzVF6plEcXgY8+kd9Fx5OTEf/fzfYj+3VprRzzGxjfmnLGd+tvWwjvtKfDVfHAnwVI39ftz3Xd5GQhE4ub/x9QH1qKiV2T0xiGbp9Gd7WNGz8BmrNTZQfE2nieKbr9Z/n660hCrBJs2j2203UhgROo9ktV7EGuxHZiSohmWgykqIBIiCGG6wDNsk5ifvmbe8BqWvh4Fv/s8hv092dIj+p9Y3POa6Lhv22fxmg8P2kSnGKzm2j9o8tFNm+yCMfe7bpNozvOQjf8LSd7+dzKJ5bL7rMdpWLmX5j/+PUsdcANJxkbgvxKJnvIlbFAVOmtdMue1Ied9ZkQRGfKXfvWaCR7QO3ju2hr1mkq5ZElThgjPAdhh/0tsYC47D5G9u4uGf3kppqsDeL3yN8d82iuAkVCGk+B4OQe3N2Bi2xXglh+nYFB/1+nulM9eQsG0E18VWVQbXXYAjSQytOeuQ72dYJtl4ULSpzy2u62I53pwQV2J0JrMosuKJtbku6ZiKkcgw3buEOQeeJh0TG4pWbVEEtVbvQU2IMo7rUNQq5GqtKa0vttD8RGh3CwR1jThOav8OsldfRs3USczoZxawEHzanW45bB8t0pnMMifbzaJLLmF84ybihoWAlxwBnmCSL5wV7fVUJAnLtps8QaNhOZ7XqWEZaJaB43iCXV6CKoa2LFGE6nDR43iJ4QErzgbdK7IFAk7jftEtK1qI/ve8cOWhe6oDmzAXb01dsOGhUD/hUBGPCDUBxG2HyUqOolY5Jm0qruuimwZGC7XUIDx20ux+k47rcCA/SvUwPuQvxphogaBOVwwGp6coaBVUWWFhxxx60p0s614QsqNUSQ5/3yPRy6iZBiPFSfK1Eim/v18SRb5+Z4FP/XKEH91jkH/4CdQLz/SYOBXvvj5geutkWXf5zr0FXNdtEDJc1ts8JtqTM9pwHBtREEmpceZ97P8h9nWz61P/jCMIaG2diEr9nivYfoJ6BAjqkYTgr+3OYRgFWoNIUv38dcvA8C2nBEHgDWvr3/fadd4aJEcENQXHQROkEE1uFabQ+jnX9NriBnOjjJWm2T11oOVxv+uoGhpPDu0gfwzWvuF8faxetDLGFVt+wfy9T7D8U39JZq1nSyQZOr27NrNo/X0seeQuEv7+1YgIwkURVG0WP1XxKFTdX2hxIkE9hhEImii+GqckSqiyykQl95yIi1g+TdDBbWkFs0DRcFxC+rFomZ7S4CymzYZlMlaaYmB6pE59eQ4ViGfGzx4/wBdu3U6u4hs52xZjt3gekdnLLws3IXuM1sqmu03v8eVKhO6l1TwDedcNq6F6uo5W7p48wIHcGLplcO6yBF9/ey9vf0njtcxXvRu/Ymj0pDtY3DmPM+avmrWSfiQRa0hQbSrG7Nc5ExOJKSLfzC/k33OL+PjEKnqzcqisK8wiGRtVB5yZoOqWh5IEfSuB2l8gLiKJEoooIycS9L7x1eQffIzCuEe5e7pnJT8pecnjbdVu7sYThkhNTzRsmm/YWOEHD+k8ugd+8HAO13XYNuyNu4W7H4PcNBe84Qr6rryMBR/7IJf8y8d5++c/wkVf/FvaXIs3ZzwD9kxcJO4rKWqZ9vD957Y1bqJVWSCp+v5xEnw1t4ifl+bw/8bWhEJT6xbFkMXmCdtxHdzlC4nN7WNivVfNdTSdPV/8Bt0L5/KGr36K9JqT2PuFr+Ho9U2DKAhYsoKFQFq0kZl9A9CZtinUSuSrJWzbpvzoBqRUEuWk5cQC8/JYnGpnDzsvu4ZSX/+s7+X51emkYwkkn7YfhOXYiIgokkwmlvBo6H6PoioptCe933x04Vp6h3aQlb0WgZHipEc9tkuIPvpcM10soW6l1ZFsY6w0dcS2Bb9PUTMai3UVo8YjA0+xaWg3+yeblayX3HUdgqKgvOxCTNsiJspIpokrCNiKiuXYDeyMq75yP08MeArjiy+9FNdxqD65BdWnMQbRqg9V9jfqs/WgmrbFg/s2ovlJVuidKHviaJIgeS0dtg0+qnQk0St4a90BM8ED1c7wcUeWGVbaKTle33pGtPiTi7Ok1ENvls6N58N/J3NTpKYnaB8aaFDHbxVxX5k9mOe6lQS5WumY6SgE7QmyJM+64RPFQxd/90weZMf4ANvHW4ujvJhjvNQ6udw8PE6xVqYtnkGRZA5Oxfj23QW2DXt7KUWSQx/c6mF6423HwbTr+7BA1FA3JDYOevfNvP2bEE0DzjmT4UmNmG/3NRChqj66R+Pd3x0LPaQFYGlPc4Lal228hzTTIC6rxOQYyc4uku95M9U9+xm/8Xbvu0TUVqfsI+tBPdLwKL5Hi6A2JqiWUy9cndzpoEjeOc/JeGnEzL54KZlg5SytOADfeaDScD5apg0BcCyDqi/keSySwWMVA7kRRktTbBzeefiDDxND+fq1Wj22mf6bvkfvq69m3h+9Lny848BeOgf2eG0T5VKIpluJ2RDU1vNOK8vC4yVOJKjHMAJVWSViF7G0q5+UmkC3zWMuLhL0Y0TR0yiSslAOElSP+if5io2O31vquA4bDm5n+/h+wOuxMWwDQRTob+v1elV/R4qETw7m+OjPn+Lrd+/hS7fvALxJcd9v7iTfOZ+/X58mnvcSpM1Gs3AHwJ4gQVWrvPK0FLFSgSWP3MWCjY/SNjIY/i6WX0gIrlVCUUNqnCgK6JZBNIdJx7zjgmt9Uu8SetP1zdgziSh9Zryk8/lbdsx+rCr4wj8yvyjPJeeozO+QqXR6ogOt+k8BHCnitTpD5TdAScMEVRAjPVQOsiiRUGKIgkjna18BksQjeyaYXLKS1BmrSZyzlk9OruSL00u4zlrGVK+XTGVHD1LSHP73/gK/fLyOKu0e86mtPlK8ctOtiG3t9J+yDNO/byw1RiKbYs6erZy6bwPvax9knqzRHXdITXkG5lqmTn3pmqEe2JUWMB2L0aInpvRArZP/yC+m6kp84ppOPv7KDt730vaW18qwTGKKSveVlzO9cRvlXIGBG+9EGxnj3NdcDtkMSz78PvShEcZvuKXhtcmYRNXvIU6KrRkHvVmXTMLybSqqmKaBdv960uediSBLIeo083eaLXTLQBJFZElGlmSsiJdcgIAllTjnLlzLBYtPC3sJFVmmI+F9xuiCNciWzpyxPaiSQkmrMFKcpKiVG+jTmuCNL9Hy6I2abTBcnGDP5KHpdL9P8ec/2sCaT9/Kt++rt2qMFqfQLIO9U3kMu3Ge7BrdTddjt9P71tejtyWJyWpoV2QrHiXfsq0mE/W/uO5JAOafdx5SLEbu4fUN/aEAesqb/9Rq/f5SRBnDNtH8/ultY/vYPLKHg/lxNNMgVyt6yHfV99f1xWYUX/1dEkVUWWHP9MGj8nPuo46gPqFnQ9ZGsXceZbPuI33+fIGLVyWRWhSHgnj3GfDKdJ3OF6U3Rr/rzBBNk1iljCuKVP05MStIJJT4MbN58xAkM7xeLc/jEBRf13UZKk4wVpqmqLe25Xoxx0SpdSK2b7JISa+QjacYLVh86ZYcj+zR+K97vIKlIsmYlscMqZr6IQsEFaOG5jOHlnT1h0UYw6qvIwt3PYyhJvnP8bP45c0DOKbFXjPBtNPI1omKdXelJTpTzQWdQBU9iJqlk1DiqJKMIkkkLjmX+OIFjPz4l/53qR9bsiVcUUS0LLIjB+jZtYWlD92J3MKKbGakJ0aIlfINjwVj84mD2w7J5JutB1X3tU4CWyVFr3m9rXiFS0nXGva9AEIywSev7eLkFkwngKorMW3VE9haeycg4FreXrmkVchrL5wEFSBXLWBa1lHt5acrBp+5YQtv+vbD/HrjEGW9yoZBT0w1WZzE/txnSC5fwsp//KTHDHAccBwSRa/oNnN/J0VUOxsS1FkQ1InSiQT1REC40W6gOggCCSWObunHJEG9e/s4l37hbv7u15tDi5noohkdsPMVDVyYiPm0SMtCQgiVBmumzkQ5x5C/iamZGrplkVDiHirjeOp2v4v4zgP1qvIPHhkEIDc6grVpIwOrLmAeZTAt9ESKqaa+Bi9GrBimJNOrmLx+rUL70H4kv+dr7taNXiWeuiWL7dhIgoQqqeimwf7pYXaMD1DSK3zw5d4mUBTgotV16psiysSPwu90toiKJP34scFDHhuTBWJK48auv0Nm5OQzKMxbwKDf/9wc9ddE+21txwbXJSarYS+PKHoJquXYCHiiK6qkIIoCUk8nXZdfxNANtzO+YDmIIrGYzAO1TjRXYsuQwVe3xDBtF6VY5DdPlpvET2wHRstTFKoyqcI4/fs20H3OWSCIYWFnppATeMJQb1IHUGsVjGSKWlu9MNA5I0FNqAa7JgbJVYu4buO4jSkiJ82Lzapop1tewj7/nW/GdV0evf4utv/oerpPP4X+k5ZgxhJ0XHw+yWVLGP7Rzxtem4zVVYNTgt2gzhrEmy4wQHBZ3r2AiqlR3fA07nSe+MsuxHbsSIJ6eFsZgLJRI6X4840oNWzCTZ/eG5NVFElGlRVUSUESRGKSSlvCe93ogjW4CHTt34wqKWTjacpGjaqpN9DTKkE/lGUiCgIL2ucwXJhgtDT5ouhF3TFa4rdPjWA7Lp+9aTtbR/dSNTRMx6Ki15gszUhIXJdz7voOVirL8g++h8Vd87wN8QyxLU8tt3GsHMzV+PZ9e5DjcRZddBHj99zv95fWP8PwE9TufTtZefeN9OzeSkxW0S2Tsl7lnj1PMJgbZagwzvbxfeyZOkChVqZs1BgtTXmbet8zVY3MC0u75rOgfQ4L2huN3g8VvaI3bodMz5tv35kvId+/iInlJ1PVPc9igL6Yd/7yLMDslfMN3lZYzxq1HFzChojNSFAFyyI1OQauG27ktEx7WOCRTK+AYzlOaG11tDFanGTDwW3olsFAbgTjMNTnwKarFbOgYtTQTYN8rYTgcszZB8f7fTgeSVDbEvUxuXdCB0FAkWR+9UR9DExXHBzHRRS8wkpJr4YFez3S8lIxauG1rhg1NNNTrY5GzPccVbUyS7bfz/5VF+BIiofmu/Bw7dBq//M7ZTItelBnIqgezV9FlRVkUUGSZHpf+0oK6zdQ23+gYW0yLIHJJSsBmLdlA10Du1GrZTLjw4c8l+T0JPM3PcaSR+9teNywTAzbmx8OtQ/92l27w39Hi+hVU/es9fy9ZrTnW7JM0lNjTe8V7LNa9eeCp+z7wbHVmPEEU4uWR7zWvfW4atYwbQvHcZ53Nwnw9n+GZVHUykxXC4d/gR9/e/1mvvvgfh7ZO82Hf7KRj/78ybB/+ex7/gcMnVO+9nmkZAJcl0UbHmTZQ3eQyHvz2t5zLyM/z7P4qbZ3NXjrBhRfy3G5t4XgHMClq5/9fvX5ihMJ6jGMQGExPsPYOa6o6KZ5THpP/vh/17N/qsr3Hh7gycEpr6obWTSDRmkJl37Z+7w9etyzCHFdJMcJkdHA77SkV3h6ZBfbJwZCgYyArvQ760Ftsb5u/82vEV2HgZUXcFqshAsUM7Mjly4CpXgGURBI1Uok861VIIOEKNhwyJIU2nJkYykEBM5YmOL2j1zIv76hg56sNzl6G38lTOqeTcSUI7/1YopAfAbS0t8p4ygqIyevQ5vFLkeMTuoRWpruj5koUiIJnvqtYZshmiJLnnBSoVZGftVlmNM5xn75W4Am5GfEjOG6UMmVuX1zM0Jg2gJxOUZlosz5t30DgBXnn4br1qnxgciP7bhY/rBrl0xOEzz0dHjNmQ3KxIE4QxC9WRnXdcnG04ji0W3YdMsgJqnE589j3pUXsfvRzei5Amve8ToEQcCKxREEgXlveT2lp7Zy8LFHw0UzpYrUfB/bpGg39cbO75BQ5aAvXfWUvX9+I0IygXP2KSSU+FEjqBWjRkqNJqiNCOrMcRograqskPY/w0hkyPUsIrXzSeKKSjaewrItkkqsIUGdNGxc3LC3PqHEEESRmqn/3nuiaqbN/z28v+Gx4eIE28b2YfismGgvGsCinQ8x58Bm9l3xduRMOhQhCxDUgIZq2s0JKsBnb9rOeElj+SteQWHHLpzR8QZULkBQwbvH24f2IwkCsiSjWya5apGiXmainGOkOMlUpcB0rUhFr9Lf3sv89j4s22pCBEVB8Ppkj5Dea9ouXYKXDIz6RcNCPMvoSadjqzGqhkM+ULiWvWvUil6/co7CX3ftQz7EWqNWGpGUvl2bWbDxEbr37SDmt35o2TZPMI4gQZWesY6C67psnxhguDjJU8O7GCpOMF6ZJjGjiJaeGEHxqY2iIHhWKC0+r2pq6LaJixv6zx6rKGpl7t/7JAfzzUnC8RJRBPXqNXPCf9+3o4YseGNo7ww7IsMXK+pKtTFSmsTFa08J5uUD+VEeG9zMcMFbP8p6lZplkJBVrnukyF/+eJzH9tRwXG/MLN98J4qps33dNQCcl8gDnoLvoWJ+p9yUhAkCdM/QOtAtg5gS89gUkugVhV9+AYgie677aQPF17RdppasQk81eqsnc5OHPJe20XqxW/CL80q1TNw0KdTK1Ey9QXQtGttHi2wdKYZ/r+jz5hnXdRkrTfn2St6aE7VEEy0r9KaPhnWYBBVgr5liz4UvZ2LFKSH7QkVAs3SKvqq95xn+/CeoASAUKNnvmhhky+ieWa9nENsi19Rx4ean8wBkciMs3v4A/W99A8lliwFIFKZJ5KdRtBqibWErClY8wehJpzO85kxGTzqtIUENUNP7dzQmp++9vI3zl8c5fZHLecuPTAz0hRgnEtRjGLU2zyw8MSMxUiUFwz56M+nDxZ6JAjVTa5C8DxLUPllHxmXCVhnI1xE02bYAAdu1Q9pGUatQMTUqfhUyJiteT9LvUMV3pjHzndvGuO2/fkYp28tU3zIWKTUEoJCo9492p6UmpbyAnx8rF4lViriCwJ4LXtp4jD9xBkiT4iMUCSVGQlGJ+eJBS7uzdGe8XlzHdbF8v1l1Fkrt0UR8NihhRsRkAVEQOKm/nmxIooegtgrP0sX7zcRZkIMAOYnLkQTVR1C9TavXfyoJEqIoeZTP885EPmkZ+/7tGxz4zg/IqI2/15jlnV/S8hKtLtEgFrHFcVxQxW7W/PprzNu/kccvfSeLelK41CutejrLA2ddRZQteWa8SNY1MOOJhv5TaKb4LuxMk5BjpNTEUXt/6bYZJnSL3vQq5JjC3HNOo2+ZZ0kTjJmua6+ERIyRH/6CsZJP04nVrQWSos3aGUqlgiAwv72PpV3zEQSB3rEy+j2PMv9P3kJHZw8LOvpQAhP6I0xQNdMgocToTGSRRZl8rRT28xiWiSrJxJX6wqRKio+KNxYmRheuJbZ7M2lBDQtdfenOhk3FhO75DYtmfYMYl1W033NP1HzV4DVff5AfPdrIcCjUyui2Qc3QqFkGY8XIxtl1WXf/D8h1L2T/uisbXhcmqDEfQbVMEmrrJXjbSImVr3wlANUHH29EUJONm1bJNFGrnvdnxagyVBhnulokr3k2Mg4u05U8luuQjaeJSUq9B/UIxZBaxXjBJHfv3Vz3iS9z0vf+kXR+lKpenxeqhkveR1ADATG5xdd9zWLTEwDxi2i7zCSG23hgrNyYoAZsmO69O0LxPD2dxVYjCarPAnomm9upaoGqXmO6WqBiauRrJZJKvEF3IDU55qNVd/vfzVNCbqWkXDN1DB/Z023ziAR9jjSGCp7K7e7JA8+7qOEzjalKPWF/63mL6Ep5v2Ou6jJa8MZQdUaPneGzxToSWdoTWQTBa/HQ/Ou8Z2qIklZl37SHOpZ9BHWyJHPL01Wmyg7fuKtARXfAdVj95E2Mz1vF1JzlzJU0Fsk1Kq7E03rj/TYz+jtksjP2Id1pCTmyBjmu6xdBFVJqHEHwvE9LaZXsS84h9+tbESJCX4FScL5/ccP7pnKTzfQCPyRDJzNWR1hj1RKiZbLk0Xu5aP9+SnrFT1Bb24Q9fbD++f3tCd598VKAsBfUxSUdSyJaZgPlXrRMak8+xSO/vIOHbnmYqYOj7H58C/sffALXcVoW4RrCv+9DtXhJYbgw4fefCseMpv9sI7Ahqlk6E5U8uycPsG1s32ELQ9PV1sWokzb8FlESmf/Hnt9prFSgc7DR7UPLtHvXRxAozpmPkco0sOmKNYev3zHNE/tzDa8ThDJ/eJ7Eq9bZpFTpiIuOL7Q4kaA+i3Bdl6lKgW1j+xgv59CybbiiSKxS8hrt/VD9ynbQH/RMI9rADqDZ1QYkBepeSPN99PSAFefgtIXtJ6iS6QslOZ7IStSaYLycQ7N0FEn2jvHVQB3XYaKc44G9T4Y9TMc6Zs65f/V/D5LY+jgDK88HQWCerOECBan+XROqQGaG15iY9RaT7NgQuJ7qq5lMU4wIzgRU0gBpCjZpsiQR8xO3QNlSFiVw8a18PNrkM1XujcZME+zZIqZ4tkAvP0XkjeekWdwt85bzsyRn2dgezI+xc3wAzTQY7u7BjCeYWLq64ZjAYqYBQRUlJFFEEWVEUUKRZWRRRPK/67y2Hro++QHUhfPY+69fYd/b/5ST3brn3ISt4gJpx+CK5AQ/79/AZ7sbxQR+/X/3s2THA5x89SUIF11BTHAo2xITWgStqwl8cnJl+PeliSkQoNLV22SlM3Nz35fJsKBjjof8ikdHodNMnZii0h5PE+vu5LWffBfnffhPw8QxoN5OCQZtV1+OdueDaIWgD0qg4tQpvmvmNyPs7YlMWEjK/+ImxESchX/6VuZmu73kcUZ/9KHC9SX4VVkmE0siSyI1QwvVqL1KvUpSSURe49AWT5FSE2QiKoCjC9Yi6BrtB6dQRBkBgZSaIBuvfwdT9N4nOqfF5RiaeWzaFl6o8Y179rB9tLkHarpaQxIkvnDLGF+9ReHubfVko+/AZtqnDrD5nNeGqHoQUYpvkDil1NbzwO7xMp0rVpBduoTyA+sbeoyjLALXvycS+WkUSWbSp571pDs5Zc4yTMfGdR3GSjl6052hrYbl2BiOhSwdfh6S9RpLH7qDvh1PNTz+yNd/xsbr7yAzt5e28f1c9eNPUhqvF2eruhO2Y3SK3tiZ2y43UB9fvS7FxYqHvozPW8Kfja3hExOryPkiMUFhKDMxQnJ6guzIIKJpNCiUB+rseirr9fcSQVBd56g3t67rsm9qiMlKnorPbChp5SZRvADNEm2vZUL1VfuHi5PsnWrsz66ZOrqvoq9beujr+Wxj6+hexsrT5LUyRa3CZDl3+Be9AGMqYjMzty3OBcu7w7/LmozjulRn2GgE7UyCINCb7qAjmcWyvcK7bhnYtk2+ViImqx61Va+imToHprx7Zr5c4+x4noruMG//Rtqmh9jmo6fnJLz76HGtDdvfJs8mhtrf0UzxXbd4pmq+t39IqXHOX3wq7fE0+44vtwAApgJJREFUoiChSDKL3/V2nOkCB976TrpHdvrHe98tN38Jo6vWsvvCl2MmkoiWFRZkZkbX/p0NRWm1UiJezCPaFhnLIhNPUTM1SlprxG/nWH2ue/2Z81F8DQtv7BoklTi4Lj17tnkWbH5M/vomfv1P3+Lpux5j8w138/N/+i/u/M4vefyf/oNtH/kU4hHSz4N7Oi6ILOqcx5xsN+lYwqfpP78JqukzTlw8/Q7HcchrZaqGdkidFttxKdSaC1ayobH86TvIvPQyYr3ddO7fxZJH7yEz3mgNaUTYMkHEZrDX1u8z2DvROP6yyQrDhQlqpkZciZGOWNMcT3EiQX0GYZd86fH8GAWtTF+6k6JWxhUlaj5NceW9N9PrezvJkoyLh3o8mxttppn1WLGAYVsNVL4AQV0gexvHg2ackbyF46MpomX6kuNBglqvMGumju26DcqujuOZnW8Z20vV1ENBpWMdM+ew9q2PINkWA6suBGCe7H33abExQQ0qjUEIae9GTPiqjpqv2GtH0KRgpTF9RFQJqCWSjCp5PSIhfVLyEreaqR8zei809ncc+jiBwfwoo6UJFvaO8obzC7xklYJmen1RM6liRa1MWzzN7slB9pWmuPOkU8JeliAMy2ii+CaVOJlYksWd85AFX8FXkjwTcFlBkiTaTlnNwu9+mZO+8s9oQ8Oc/fPPh7RPG5FpWwHX5VNde5CAs+ONVPf0DT8mnklxzkvP4uNdXqVw3FYZytXvCc1weKDWyQ+L8wDoV3REQWhCTzXTaLLUuHjFIua39SKLEqcurCcNl64+dNLnuA6mZZKQVdoTGQRJor2vi1gqHiaOZjyBbhmUtAqL/vB1OJpO6c4HABjKWQ0iSTPFMaJhaxrjv72NnisvR87UK/MBQmTMoHTZjsN0tRD2UVUNzaNoixIxWSWpJmiPZ+lMtoW9VwFdOcqs6G/ro7+tl9P7VzUofo8uOMW7nhs2I0meMFZcUUnG6seYondPRX1u44qKZumU9d/fBPX2ra0r4xXDZP3+Io/v0ynrIpUIarhq4y3osRT7Vr+Ek/sbN6khgqrEQtuZTLw1/Wr3eAlBEFh65ZWUH9uAWW3cVA6eeSFjq9YysdyzJEgUc8zNdhOTVZZ3L6Az6SFKkiii+6IjU6UYD+2qhQIvmqkfUvQniDnbNqFWK3Qc2BdO1BMbt9Hx428yZ8UiTnrPn3DrG/+RRCXH8PveT2XXXsBDUAP10x67Aq5Lx+gB/uXqOJ9+TRf//ad9/MG6NFm/f60yt58dRppxO0bOVjAsl59OdTHW1ofgOCzc8BDztjzJsofvbNiIxyqBOnsmTFBlvwf1mbCADuTHGC1NUbMMRFFk79QQgiA29S4Gvyd4CXHAlALYO3WwgfpXM3V026QzmaWs18jVnn2ht2poDBUm0EydmqEft5R703Yoat4aIAjQnlTpSdevdakmMpK3m/YIM4Xvk0qcslFjqlrwxagqWI5F1dR4bHALVVNHEEVyFe+NfjR3E1/q2U6yUuSkDTdSS7axf9VLAFiqeL/d07qXICQUgfdHBPZEwfOXPHupQtUaZrqaY9Uc717u75B57ZmN87hueQq+KTWJKIjIoqcGnVISdFxwDt3/+VkEQeCKn/4dmdxwXYRJFMkvWIqVSIZil0FBZmZkJryCcbm7F4BYpRS2m4mOw7xMF5qlU9DKTftQ13W5YVM9OVo9p54Ymb7qtyxKdA7shkcfY/M963n0+rvY9ejTbPrSf9K3ZD6v/Z9/5ZrvfoGzXnUJ13z4bSz+0HuZ+O1txG/+RcvzDSJQ6g0SVMGxSapx2hLpCCvh2CWoRa1y1O12Ab035u8NJ8o5SnrFE0VzZ59fCjWzJeC9ZNt9xPQKc//o9SSnJ+jds7Xl6/VkqukxWRKYSRCr6vUHPnhFglQsRleyjbisko4lW7p8HA9xIkE9ynjw459k99s/QK1aoWZoLO2cR0pNhCIFE8tOCqvanYN7wgVdlRUMn7/+TGNshhT7dLXKvLZGP9AgQV2pehPsgJVgumLXEVTLRPLVWmumjmXbXk+q/99VvYtChDAQzQl9xozaYWXKn2lYM6pQi3Y+RDXVwXj/amQc+iQdF5h26wuXIJiUtcbJwZiBQAWWDDMTHADL9ny9ZNG7NorkJWJpv2cMQBZlJFGiamjEIrYszzaOFEFVJBfLsljRs5DFnfNIKQk/OR2mqtdC43LwkhkBgb5MJwk5xtKu+TiuS0FrFBgxbW+ijSuNFN8Ll5zuIW9qDNO2PIqvIJKUvUQnIcfQLIPea65k5T9+EnHvTl793Q8Qr+QBGLdjDZOxIMDaud737Bzby/x9Gzj50rNRYgrzVC/ZGbNjFCO/oeZXjkuOjCh66KRAI63Rdmz2TB5g58QArzmrRnsSXnVaN2cv7mJ59wJkUWJuh8MrT9e5+tQErz2rtepz+JmmQcyfyGOyCoF9j+2EvTZmIslkJU9nso1VF19GYslCKj+7Cde2OW9ZPBRJWtHp3fuvPTONjMOft+/nfWvqid3Q936CXSoz902vDR8TTQPZ0HEkCTPeWOkcKU4wVpxiqDBBzdQZmB5m9+Sg53Eqq/Sk2+lKZf2F3FMQdV2XuKI2iHn1ZTo5d9Fa2hON10JPtiEsWsHAvZ6oRjqWRJFkkpHxWXEVBIQZCKrqW2f9fno67pussG+yNcpV023Gis2bkli1wNJdDzK87mX09aR4/dkzqLgRBLVqaF5RKN664LVzzLtnV77qGhxNp3zPQw3PVzu6yS1YGt4XilZFlRQWdcxtuK9tx0ORpsrw2RtyfPueAjdsLLO4cx59ma6mpCsaommSGRtqEECRDB2zUGTbez6Mk0hx8TtezYQbZ2ruCu54/d9jjY/z+DVvZvPffo5NW8bZ5yeoHVaZzsE9zN36JMu2rGdxj4IkCqjVMmqtiq0oGO11fYFBy5tzHihmuKnU3XBeUW9IF59REE/gyAqWn6CKAcXXPjqKr2lb7Jk6yHBxgv62HpZ0zaMn3c7SrvlNx8YilEy1UkKRFAzbQjeNkA4YRNXw/Gc7kllqpkauWmLXxKHF8Q4XniJ4jdHiJLbrfU/NOnRva65aZMf4QNie8EKIXIQC2ZFUkUSBnkx9XN60yeBvft7ce2lYjXuRTCzlFWIqefZOD5GrFjH94sRY2fOiz8ZTjBQsOsQIw23fLhbsfoydp13FVevaueykBOu6bEQRzHiS97+0nX/7ox7OWhLnz1/WzuvOSvOlN7fzoatrXH5KgYSiMlGe5iNXdfDhKzv41LWdTRoTNVMnLsdI+UXDoKUm6fejJ9auZvG3v4yLwNU//iRKC9EhzbcL7NmzDUlvnHclQ0epVXEkicK8Rd71GB8hXqwj6rLjkFDiVIzmAsmXb9/JaLH+nqtaJKgiAlu/+E1++g/f4sHrbmHTbQ9x13evR5ZlLv/TP8CeN5/aGWex+m2vw3rLW1n4/j+l85ILSP3qe6j+HmTdoub5ZmDa+64BxTdafAr0FY4VgmraFk8c3MpjB7Yc1evytaK3B5RV+tt6qZoajuPMqtodxHSlxf3ouqx+8kZy3YuYc/pq+jc/Di7k5i9maM2ZjK4+tX6+ydb08kPtwhXZIiap9KQ7yMRSR+xp/UKMEwnqUcb8yy9D27Of/Hd+THsiQ3eqw1cL9AZprb2LfeddFh4foA6KJGNYz7wP1bQtHtq7u+GxuJSiM9nW8FjNdFgsV7k65QkDPK61kas6WBGKb2DaXDO1kP7UqifGo/nWKVIVozYrzeXZRrFWn4AkU2P+3oDeKzJH1hHxktOKXR+yomDhuI0nVFUbN3yBcFVh7gKmFi9ncN2F9ed8kSRF8hFDUaI9niapxuny6Vwe3VmibFRJKCqZY0SVOFIEVZYcMvEUc7M9YSXMcT3KS0KNhxO367pMVwu+uJHMmnnLiSkqKTXRhDTqloE6g+IbRExSaItnfLEUbxFtS6SZl+0mocTChKTnqpcy98tfIl0Y45IbvoBk6kzYjWiQKMB7YzvpFA3WPvpzTDXB6ovO9KrPePfLuKVS1prNpgP1z/CcI8iiZhok1DgpNcHZS1J88U3dfObVJwHe7yWLEgk5xtnLFK4+TSKbEBt6w0p6hb1TB9k3NcRAboSSXg1pMKokI8oKrusiaVUEx8FWFBzZs2HpSGRZ1DmXZX/xXuxd+xn++W94ycokiaSKIMDlK7xrcMXaJH93SpE3t49y+YHHADBzeQa/+V06L72QtrNOr1/zED3NNPHI8rUS3el2CrUSNVMnG0/RlWr3E1TPBqi/rTekMwZqxEklHprZt4pohXzhpZcycP/92JWqX5yRiXjGo+HTJq36Par43pxVUzvuFURbxYaB2amSmuWiSs3fedmWuxEsi9f/7Zv559d3NwhNQWMPqm55RRFJaL15GJjykuMVL7+SxLIllL//qwaabxCm33M/m/1EXImRr5XYMZwMi0c3PFkhHUvSlWpr+Zog5m57kv6nH2/YDUmTE2z98Kewczm0N7+PVHuWMcubR0YWn474Xz9m3ptey+R1v+AVP/gYwxUBB8iYVbr2e/TFWCB45NMFAcpdfQ1j/2u5RXxk4iQ26G38Yn/rJN5xXUzLxbRhCl+ZPUBQjSjF98gR1LJepWpoyKLszwcKmVgqtGmqf7gTIrfgqQwH/qj5WgnTtjH9+SZQyHfxesHTsRQD+VEGc6MNirNHGqZt4fqFx6pZo2zUyMRSDf2XrcKwTHZPHmDj0A62ju19wfgYRzfxHUlv/uxOzy7s8obMCD+cuxGh1jjmJVGkPZFhqDDBVDmPbpuht+9UJU9Rr9CX7uTgtMVpMW8Muq6Lef1PsWWFbeuuobdN4h0vaWNhXEcWBd740jmcvTQetpOctSTOq85IM12bZG62i4Udc5mT8bRHYorIKf0SitRaxTmlxsn63quy31KTUOIooidGGF8wh1ve/M+oWpl1t3yr6T0Cdp5s6MzbsoHuPdtYsOFBBNsOUVUt006pew5GMoVarZCN9KRKlkU6lvQQ/Gpj68IvNtQp6YoksKirjtwZtoll2+T+96fsuOU+1lx2DhfcfB2v/uk3OOOqC3nlX7yFTGcbWrYdM5HkwLoLqLV3IQgCS/7y/TjlMu/c9UOuOT3F2y7MMjMCQcQQQY3Mc9IxTlA1y/A8jS2L/31oL2/41kN89c5dh33dRDnP4HSFHz4g8r/3l1nQMY/Fnf3YrtsErkQj16L/dN6+DXSP7WHn2a9i/p4tSIZBpbOHsVWnUpozPwRVoFlvADyfc+cQS64imai+jkpfppO52Z7ZD36Bx4kE9Shj0ZUvp+Oal1P7yY0kSxoLO/pC9CLYqBmpTKi0GHhDxSQFw37miMNYaYqDucaKvkt9c5OeGGXR+vvoKU3yvbler9CkrbDPTOC6UHXrXoYegupiuU5YYWyVOCuS7J+zDq5LxdQQeG4y1ChPv3/fkyimzsBKzz4loPeOOnG0SB9KXBV4x0vqCrbXnOFQlqSou0q4gUMUmVh+SuiTB15fqeojiZ2pLAgCa+eu4ILFp4XJmyrJKKLkCZooMTKxZsrFMwlFOrJbTxAs0mqC3nQn/dnecMIGSPl9sgDT1QIT5RyKJNOZzHLuwjUs6+oPiwz17+xtbpJqrGWCum7+apZ29bO4cx4JJUY2nqI9kWFZ1wJishK+HmDeyy/i4Svfz9yBp7jyJ3/LhmkJB7i+3Mc2Iw0CnOZO8O7cXSzddh+7z3wFsWTC6/n3P2/MjlGq1c8vkE0vRRJUR5ZDaw7w/eRkr0I4N9vNuvkn0ZnM+tfLExTIxFMk5Bg1H/XbOTHIrvFBbMdmYHoE07I8ywHJq34nFJW0mqQjmSXrC24oFd8zMpHEsEwEBJJ+YrzgNa9CXbuK/f/2DZJWlbNXZVAkgZTf+xpXRM7ssZH8Tatk6Oz/yn9iV6os/dgHGq55zP8cfUa/ieu6CIJAZ6INRZQp6RVUWaEr2YYqKaFFiIfye0l41e85SR2ml/Wrbz6DK07u46NXruLyd70dq1ZDu+8xkmqceW09tMXr17tgKyB47IsgvOKF4Ns6NPfYHO8xPosvI3jUworenPSs3Ho36skrSK9c3rI4EFXx9VozZNxZ5tOy7qveyjKr/vzd2HsGOXjHnVQNraHP0Ix6b7coFCxo7yObSBOTG8dDWTt8cpIZH8HUDLY/+CT3/fBGHrjuFu5/5VvI3/8wD7/8fcxf7NnRVNV60a4az7LiMx/ngbf+I23TQ5x63/cZsuIIeMXRaCRzUyQODjIyMMLWXSNoB4dDBeyco/K45iXQ8bbmseyJ1tX/3jTtbW4belDhqBPUqqn5xYNDK1+qlVJDH96cbZtYsOEhRMchXythOfX7wkskPUq3IAj0t/VQNWrPaONdNTQe2r+Jp0d3M1nOUTZqLO2az9xsN4ZtzprwDhXGeWj/JiqmxlS1gP0C6OsLIpqgdqW8eactMRvDyOUD7QMskDXmTR9senZOthtVViibNZZ29eO4ju8ZLbG8eyGFKkyUbNZUB7jrv37Oz/7uqxjrH2HbumuopTtIqaLXTxxhzswMr+/QoifVzsqeRcQUNRTk2j6+n+3j+xuKdrbjoJs6STVBW8JLOAS/FzyuqLTFM0iCiCA45HuXsumCN7Fg96OMPfRow+dqmfawVSk1PUH3vp2kpidJFHKhiq6WbQdRJLfAEzgybRfT9iQoRdsiocTQLb1hH1ozbIby9WT/m285s8Gv2HQsaoMHGPvG/7H0zJM59y2vRFm+DLEtyzmvuZyu+d480CqZiq9aRt+fvBnzphu4vPo0HSmJv7q60XVA8FWaQwQ1cr+qsoJm6kdl63KoMHxmwy1Pl/n0b7axfn+OL92+MywINh9vMlKcJFct8sv1LttHbB7cpfHoHg1RFHzf3aNDUE97+KeUsz2MnPVyEgWvZ3909alhgc6K7HWC+T0ah+tflyQLVVJY2bOI8xefSt8hnC9e6HEiQX0G0ff/3gm2w/T3fsGnf7Obv/3lFKN5qSERsOJeRTfwRE2qcSq6xvQzFBkyHZs7tjb2ITmOhGBZzN/4MPM3PUqikOPa6Q3h8zeU+whSgWDDLxt6iKC6rhP6nLbi5Md8lCRXK2HYFqblN4o/B4hJUatvXhbtfAgtnmF0wRoATvK98fYaCWoRJb+kKnL1ml4+dtUq/vSiOVywXKVqm2jpOjJgJFonlIHarSLKzG/rozPhvSawWAnCM9b2/o7Jh9/4H2nMrIC98tS5LY/rTCZIx5O0xdMofj9sgKQklTiS4E3quVqJjmSWmKSE1E5JkEIUIQjNNwuPCmtFIyarLOnqR5FksvE0Z/Sv4rxFaz0BJclXdw4S5JjA7rUv455Xf5zu0Z243/4Sr316If+WW8K4rSIAlmFS+sV1lNr6mLzo1YiiZ8cQ7MvHLZVSZLOshQmqFG7djWS6AV0JvOzSsSSnzFkaJqfRyMZTJNQ4NVOjZupIgkBCUUOEIaDz9qQ7/O/t0a9EQaQz4z2m+IihGU9SNTUSqpewg4dMdf7lu7Gmcgx+839CDzcxgjKqtfpCMvKN7zD8w5/R/9Y3kFq5vOFcQ5GXdOP38JBun3YeS1LSKiiil5hmE+mwWBSgxpZjU9arXqKdODSteUVfhm+//Szef9lyFlxwAe2LFzP9m1tZN3813al2FnZ2hccWfSN7ybIakqBAFOb3heZrOTb7pobQTKPB9mJm3LUlxq0zrJTaJwboGN1D5hWXA5CaGmPhEw+QnPaYLKnJsVDcxFZinqegpOA4rRNUzfR8HgHOfts7UOb0MvKN/2XPxCCTlXyoxOnICo4sI9o2UgvrkpisMi/bQ6HaOOHsGjs0cufoBg/+5Fb+58Of497v/5a9T25n231P0Lukn0Uf/hA7T7+KFUoVQQC1p77hLNYcDMtlT/9p7DztClZtvJmtU1ZTGi4YOuPf+zHf/+uv8Jt/+Q5PffTTPHrZq3nZTV/k7FS+4VjD8otUrsuDygKGu+bzq/IcvpFfGB4zqPkoqyiGSr4xyz5qFd+q4fWKHsrruqw5XH/7QQzLpSrVN5Op6QnWSgnPYzbC2PB63mok/TlXEiWSatzzGT/K/tipap5ctcR4aZqR0iSq5CElsiR7xSLTaFqfdcvwab3T2LYdMnBeKIWl6Ca+01fvTcVb7zGWK5H7zmr+XUVBYG62m0Udc0O9iJqph4jlI3s0ZL2K9X9fZ3jHXnoW9zP31dfyxCXv8D43JiAZegNzZmYUtQrtiSxzst2s6FlAUvGuf8Woea4A/m+hmQZTlQK5WtHrqYynwtahmqmT9NV8Y7KC5DOjFFlg65mvoppqZ/e/f6vht3QliV0XXUW5u9GnuG1kkM4DXt93ucez6NlSS2JYLq7rTdmW7dmEKZKM4VjoEaXpaCvDnDaZ7rZ8w/ublkXu699DVGQufOOV6G0dIAjhmgce+tnKIm1/bgT7La9EXdjPzn/+IppWY838GNlE/XtZvo5IgKBGKb6ZWArNMjxV8lqzYN3RhuYnqDvHGsf+nolyy+M3j+5m29g+apbO4FS9aLJ+rxa2yh0qQc3NSFAzuRHmHNzC9jNeQXtSQtZ1XFFsQE31VIZqRxe5BUtaKnMdSgFclV10SwtZVMdKM+X5iuOXnPw8Rmz+PNpefjEDP72eX7e9GluJceOTKhetsEM558DbUfF7BVJqkoO5sbBB/Wjl/W/bPMEMABXD9tRq05N1D6rgtv9mfiHXlepJzwEhzSogOT2B1NWJ7TgUtQpxJYbl2NRMLTynRH4a0TJQkwlqhu71cvgebqav+nusB36AoIq2yYLdjzG44nxcSebS1QnWTHkT0/pymrvW1yeSlCrRnkjw/y7tZ6Kc45GBCpOVPPn+RczZ7qHIjtL6PE3bs+KIKSr9bT2AG9JvopFQYr4li0fvPVbN5mv721jclWT/VJW3nbeIv756Naf2t/EvN29vOG5BRyfr+lf7isIykiBSMSq+2bccNugLCGRjKcANc4hA5CiqMlc1vEr+kaq6dUSSP8X3jLUcB0GwMf2FZP/ql6Als1z+y3/m2v98D64gsC/bxh3L5rBvg0fhe/j1n2ZBQgh9EINpd9yOQYsENUrxrXQ2UlQ0y6Ar2ca6/lUtf7OF7XMYzI8iCiKaZfjCURl02wiTe4+q7SL6BQlPwMJXq5UaNyVmIultKHwhKfA2/uk1JxG76mIOfvfHrLr0HHppFBJSCnkGN+9Gr9TY8cMb6XrZJSz71F82nqzrkpoeb/k9K0aNpI9yJ9U4uVqRmKywqH0OuVqR+e294e8iiRKaz4JY0NbX1Gt6qBBEkbVvfSsPfPazCLkSzE03qPhWbBFHEBFdB8FxQhVZNWSF6Bzayv74iK1je5ko5ShoZSbKsyeoY4XmOWDp1ntwRZH2qy4nOT3BgicfAaBL3IWtqCzY+Eh4rO5TyFVJaerpTygSNTNgtdikYjI97T0s/tB72fXX/4D1y9vpevsb0C2ToE3PjCeIlUvIWq2BaRCN8Rk9s/snTc5Y5ImAKVqNzsHdFOYupNwzB2Nikh0f/humH3mCky5ax5LTVyP/wavp2bsd2bKYtiQ+UdnD2lgJWQKjrQ3w1rnpis1w3sJ1YdMFf8iyLXdTvP032G+7Cq1cpZovoVVqbPrsG8gNDjNv5SJ63/1OxOXLmbj5Tob+98eces+9XPbxj/J5/TzAS3rvXXI+ux7dw/cLczD9uvq6WB1VGbNUHNdFFAQsNYZkGMQtj5p4NAlqzdTQTYPUIejP1z+S422Kh97dVOvl9eqB8LmkIDK/rY+yVsW0LWzHYaqap6LX6MvWiz6SIGE9AwGnquGhX9PVPLptsazb640VfR9c00du45F1b7KSp6iVKevVEMGLJtDPd/x/9s46QJKzTv+f8q52nx63nXXfzcbdIAohCYEQIMAPOeyw4w4JcLgdhx0a3J0IJMSIbTzrvrM77j3t3l31+6N6eqZ3ZjcbEuxun792p7Wqq973K8/3eeoovtUE1a4unKDOeJMCrIwdYnzEU5u5PBJjiTI/f8RGwJnHoUl8fP8YglHh3Nv/i8LEBBe/+WU0Le1ipKxhjlZF7jQRtZoILdQ9BSvh99ndeKp7j022LLpShSw2WcM0DYqVEgOxMWRRpGIYdAVaaPbMJpZ2xYZdsVk+7NXkuWIYKBIUFY0dJ1/Nyfd+m7F776fx/HNmP1wUiTd3WHPh1VPkGbWuv1hrF1lfkIph8l+PGZwxZzsxTUini8humXKlUjf2c2hqNqYKuQSms8m6GHXyyafI3buZpde/CLvHSbSq5zE3eT+yiDyDfKmAz+2j8C8vJ/Xvn2Xfzd9nxZv+H5JoMhMFzKgxz3RQ51J8RUHAo7tIFTIk8ulnta8thEK5RKlSJpGtv++GYvNHJEzTJFnIMpWJz7NB9Nit8aeKadQ1AI5ELFt/j3XvuhcTgd7l53KSZl33Rd1ef+5EkYENZxz1PS3l/IXXeacmIgkSNll9RhbIPwNOdFCfJUzToFQxaXrZ1ZipJJ17HwQglhHrNptytTU/MxskiSK6aiORS3N4enj+Gz8DZkQz5qJYMuv8qObi/pwfZY7p3G7DiymK6Mk4atlKNqPZJD67mzZfBLuq0+5rBNOk/ckHad36GO5CgVKlVOfbZlVenz+Tces9DbJF69w19m9HK2ToW2LRe0NOkZWadYwzinozcNnkmlKpx+bErtjIlgrEG9tINLUyvnjlMT6zXFPlnfGpdNvmd1ttslqrUi+UDP2lkESB2992Jr9+02l8+IoVODSZG0/vnLfG++x6LZmcSUQyxRwORa9Ry0uVsiUnLqs4NHs14Z4VeJrp7KcLWabSMRya/hfN0qq1Tl2ZQ9FhDk7NinyMta3mlhu/xLbTXsqOU65BaW5heM8huk9aQeeNr2K4eyMvWTZ/uRkvq2wdKPDWH07wnQcSTGes6yBtyLUsNtHYWnu+YRoUqx6gDnXhY+gKNHNW1zrL77FSts6XpqOICoVKqWalMlNkcWkOJEmqdc6lIxb2rDdQmxmcOW9e3UmjO8iS9/4rpiyy5avfA0y8IwOomRTlWJzbP/Rl/viVn3Lvd3+HottYdNN7EI6YZVOzaZR8nrKqUnC6KZSLjCQmKRsVUoUsTs1OiydsSfxjJYUt3gbWtyyrfX9ZlGqFkxZPA0Gn91kXkFa/4hWYhsHOn/4UAH2O/Um+ZFCeqW7PCWw0WSVfKswT4fpnxXQ2SSKfIlXIMjlHkO4Dly479gtNg+7dfya9fD160E/j7i21h/T4NLZUvO7pJbNizRArGuctnQ1alze6sc857zNroiLJdFx7Feopa0l/55fImULdGjwjrKUcxT7CNM15CWo8a9TW+vYnH8Q1MUrzjifI7O/lqStfQfzp7Zz9yss56/pLcVxyEYnWLg6efQlFmx0n5ZrGgYCA7pplY8QzBoNR6xrJuMMMvfi1pB99mu+883P86L3/zW8+eTN/+NJPKGeznHfji7j4fW/Ac+VluFYuo+s9b+Gku36Ne8MaJv/zY3TuexiwilbbEhrfSbTWklOAqcrsNT5e0ZhKWcc4YyOmlktV8aBjs34SuTQPHtrC3gnLK/KYFF/D4Nrk03Qq1r7+cFRnur279rBUKtbWyPH0NE8O7WY8FcUUqGOtWAr5lRqD6XiRKWbJlYvIksKiYGuN3QOgiDLFBezsprNJ0oUchUqppoZartpm/CMgmp5L8bV+U1Wp77q/zjPIW719LFFnq/Qm0Lh7a50/81zctjXDYFRmaz88vN+6r06786u0H3iUk666kKalFg22QS5gDaeAyybWhIXmUlZzpYKVqJgm+XKh6mdq/Z6arKLWElQVRVLomx7BJqs0ukP47R7afJE6qmWbL0J3sIV1zUutfb2a7ASr3t5711+K2dRE7/s+TmrnnrrjSociHDjzBUx1Lan7+0yBM5quMJWfv9cOjeVqI0HFaqIGcGhy9pwGnFZsNLeoc/DL30Dwull9saXfMSPWVJlTBFkombc81WXcNge20zfiOX0TiW/9hPTEeJ1PealiYphmnYrvXGg1ps5zV6ieES9L5urXg4US1EwxR6FUJJ5PMRqrj3kFLJq2UG0AHM1qZu4M6tIGJ9277mO0fRVZd5A2pRpTH4XltxDKlTKVo/jbAzhtojXrrDuPqUHxz4ITHdRniT2jST70mxwC7Vwabmfplj9wcNUFAHWt/hm6gzxHba3BFaB/ehSnptPmbayrcj4TRhPzk8J0wUROxGv/N4GxsspTOQ8jZY2ukMyhyapaakYg4w/hnBqnYWqSw6JItpij09+EIAi0+61u61x1uEBsml6n5X0VyybRZJVcqUAyn3lek7Vkrp7eW1J1RjvWAnCmMYRDqDBS1pis1FeNGr1qjTalygpOTUeVZPJGmdHl64/5mcVKGUWUj0nlAoviO0OXeL4Ekmbg0GQ2tM/2nlRZpMmj182DzA1YZyqtNlml2RsG06RiVNg30WdtcpLEOd0b5jzfMgMvGxXGklGmMjE6/E20+xpr1NZng7lU0kK5OI8mnPY0sOXMVwCw2DXC24ODCEDG5uSmJQFWTE9C3HquIAiYmExWg8xU3uCBfbPHPVlR6bc34AvY67zAcqUCNsVS3J0nXDIHomB1RhVJriowq+SlAmOpaM02xzGTbB5xLYuCyMydfOjU86yZ8ok+VElBryaKDa4AfruHXXY3Qze+lOj//IChjUtoWdaF7de/5OHv30J+eJxzb7wSf2MIb2OIRHaaSbMBWypOoO8A44tX4ZyyrAFmfF4HYmO1Cny2mKfV00Crt4Gx5BQhhw+bos5jXyiSjCiKaLKK1+5ieUPXM/+YRyC4ZAlNJ53E9h/+kFPf+U4c6uxn5EsmRY+GWi5hSyfJVNc2j+6kd3KQsVSUrkDzPzWdqFQpYxgGyXyWDn8Tk6nZ7tySRolzl+nct2dhIaKGwV04k5NMnvEqXKUiSj5HWdMwRQkll8U9Vj8rV6yUUCUFm6Ly4nXNPH44ysB0lo+/eBWv+s7jUI0Xc8XZ/cSp2Qm+9TWMvOLtxH/8W+TXzKpAzySoM3NzRyKRM2pdihnEMwa2ZKymkQAw2TvI1vd8AUWEK957I4HmBqa6ljDVtZQDY0X6pkqcpwbpmfmCAiQbmvE7Zu/DPaNF9ozO7lX2F19F8NQA2vZetMYGWstpzJFRujYsR7PbGFqyuq57YGuKsOpbX2Dr9W/krFs+TevSs3jkon9hIDqfPjg3QZ0sW3ZVkpQmJMs4AKVYQJKsIl7ZqNTuG8M0mEhN0xsdxqHaKBsVhuLjlldmMYdc9bteCNqhQ3RVkyQDGBCcTHQ3o2YzOCfHkIsFZFGmZFRI5tIMxcZJFTK0V/fZGYjVjtmz6aCapmklmqUC7eH2Glur9t1khXy5SKaYq3WaDNOaiZ2xxMhVR3nK/6Ad1BmKb6FcwGkzSeUFwlKBV7qton7dVVxtwjmnxkjOKWLO4KH99fdr1677WLz9Txw67SpuPHc549UxlLBUpEEussZXYtnwJLaqOnM6YBWPTNOkd2oQRZIZS04hCiI2ZVZkUKvuM+Wq5Z9klHHbHDS6QiiShF2xWcX/OVAkufa3GQ/yUqlMd0SiPwqGpND7ho+w5OvvZ+vLX8+ST36Q8KUX1V5fUTVSwQjBQ/tqf8tVE8eZYtT3ks281DXK/qKDNVqKYnWMKpGV+fwdce5r28VNl62qo/j6HJXa/m5XbQzt3kn0zw+jv/oluKtNihlHhEwgRMHhQsukyHnmzzlmS3l0xdK68Nk9uD/wbp687Dr6Pv811JPfPPszGlaxxlyA4gtWUTZRST8vCeqMXUy6UB87DFcT1Nu2j/C1P/fy0pNaOW+ZnUwxR7Fcon8a5nYtZ8aSxDk034XikbnFl1OKAwjxMbad9jIAmmXrfBYXsJI5GjKlfC3mXQgum4hT03EepXj/z4YTCeqzxM8en64ZRu9YdTGn3PNN/OOHmG7oYioTx6FagfMMxVfNzt78dtVW9Q+0NpFMMUuhXMIwjbp5uCNRNipMpuZvJo8fylFqjmEoJhPL1/LDUS+/3mJd9LIEp/XYagnqdKbC9KI2bBNjeAYm2F8OM5EMoFBiSePsZrxnzxSdhokkCninxinbWxmIj6FICj67m2QuzXQ2SYu3Yd73+UsxQ+8VjAptBx5lsPskKrKKiMnauOWX+ZX4fBpPq99Wk20Hi0Ztk63zeyz7BJiZY1xYyXYuNFlBFiXsqv43MTtu9dcnqA5t9hadSRBtskaD0890NokkSMiSRIevad4spuW1VqV+mibtvkYaXUFWRrr/ouqaKlnnolAuIglStau3cJDzy1QjL1ur0jDUi61SoCukYBuoFzroK+mUj0LiMBHY3LSOjZ31gWmumEdX9AW73UfCpmgokkK5UkGRJEudVpRRq7ZCXpuTZQ2d7Bw9SGegufY6yRukIEokbRpFh8tSsq5UsMlqXVFJkWSaPCE6XncDmd/ewZ1f+wUtyzoZ3tuH5tB54VtfTmjD6ppqaaDvAFmvn6ZdWywRl1KxJrSSDlqzQ4VykRZPA0OJceyKhkd3oskqSxs6aXAFCFbVpReCU7Pj1hzPenxgBqtvuIE73vY2JnbuxBGevd/yJYOEx48zk8YRnbCSaagyC3QSuTSxbJKIO3i0t/6HRzyXIlPMUTLKlA2jbgY1U4ximkdnjXTvuo+SquM8dyPOvPW6gtNNSdPx5gZwTNdbZFiWE6o1Qy4KfObqNbXH5hakMnONHgUIr15F4fyzmPz57/BdexFUGaMzCtfqjDruERiIHtmlM4nnKjgmxunbuo+RA/1MHB5manAM3efh8re+DHd1rjQeaeXHm5PctctKfndrdr5o/fw8YDbRtnQ1PvPoYw+dQQ2hbTXdl19pFUKffBC92wrMB9edWruW5kLUNFZ98wv89F3/Q+dDv8MVH2XHmz7LkYSv7JzPHa9oTKRy6LY4gUqRACAXCshOWy0ZUySZXKnA4wM7MYFD0WEiTj+yJBPNJkjk06iyQutR9jbX2DCNh3dSBj493cXWgpsJU8EUBDK+IM7JMaRiEUWSKFfKjKamcGp2FoXa5t2TkvDsFYZzpQL5chFBFOclp2Ctd4VyqU5PYjw1TTyXQpVVcqU8mWJV/KdSZiA2RpM7VKe58PfA+Bx7k7Db2o9zpQJnLS1x/16Nc7R47XEBKCMgz0lVXZOjCyaoc+FMjHPqn77GePNyzn/nyxEntjJcsCFiJajNcp4POvYiDlr7oikItVnPdDGLLmtW/JNPo1XV02f2UL/djU+3/G2dmk62mMeh2lgSbifo8FKu+noeDVaBUSKZT9Pkk6GqSL1bbObUb3yC/E1fZM/b30f2wGHa3/762ueW5iQ2JZtOpVo4nElQv5No5TuJVt7q7WONlqJStPbqzftldo+U2D0yxEQ6xdjs6cVtt7qnxUoZwzT40+c+hSBJBC8/D2lilIqi1IR7TFGib9PZ2ONRst5Z+voM0oUsDlVHlmSCDi9KTxD3y64k8aPfEoqczZDbYriZpnUvGKIMmPM6qKqkWMyA55ig5ktFMoUs6UKJcqX+9xiKWffFW35isV9u+v0uuhsWkSvlCTi87C5KwOznp+ckqDOFJpX599HUnFGR0JN/YkzW6Ft8KgCRaqHvaDopC2FGDfrfXtDAZ+6Yb1Pl1hW8unNBXY5/Rpyg+D5LPLB/Ntg4tOIcKqLMop33ACAi0hsdtCqVVUlwPRmr8w9UZYViucjh6WGeHNzD4wO72DF6gN3jh2p0zfwRYhfT2QSTqflUoLBUxC2WiZVl4k3tPNo3+5yXn+KmIzh7w4zEc9wZczBZUgiYeR5+ssQ9uwv8959iNeGhPSMFdu+ZwjCgUjHRMinavQ04NQdtvkacmr3moXU0SsNfghmT7vDQbvRsoqbe2yLnUYwy4xWVh3L1FTpBMOkMuGuerQBOTbcKAMdYyAzTZCA2xnQ2gcfmOmbAb32OQGegmQ5/4/PeQV0I7f76xcoxr4MqoSkW5VitzoRqkoIiyywO1ifxMx1XgJDTR4u3gVWNCyuMHg9mKMaT6RhatZP30pOP8mRBYHrxckv9tVQCw6iZhoMVaOwpHrsLb1Pmf89kIYNd1arztseGTVZRRdkKwAQBtbpRhpxefLqLUztW49VdnNG1jmbPbKAs6w52nnoejyyyKFTFclXtWdXqrjeAoMNLS7iVtR9/H6ZpMrTnMK0rF/Gi97yalqWd8wJwLZ2qidnYY1H0RAxTFEkHGqresyJe3YkiyeiqXptzCjq89ITa6maCj4Rbsz8nn96V112HIEls++EP0ed0UHNFg0SVPuacGqsTStJVG/lygXRx4e7iPwviOctTslypkCmUamuSLArYVJOyubAwhSs2yqLdf4bTz6K5EVxV64uCw71gV6HgdJHIp3HrzgXXnrnnPTung9rubcRjc3LyO99BOZ4k+/Pbax2wGXEtW3phAb6B6EwRyeRL4V18q2En5sAgD7zlg9z59V+w66EtmKLIklPX8KJ33lBLTpMNzTw0KtaSU4Dthdnr72l3F4aiIouVBW13ANpDKpIo1r7reM8KSjbbUZPTGSh+L+PXvJE/X/FvhEf2sepr/4YjMTHveTeMruZ1YyvJmRLJXBmv7qKkqoCJVCzULOBmKIvRTIJYNkk0HSdbzJEvF8kW87htTpY2dNIVaFkwYZOzaRp3PEHFgMMlnT9kQgyXbZQqkC2atdlfqVRAEiUCTh8Bu4dmT3jBgtHMzGHpGHS9IzGjMHw01o/lTVyozqhBMp/m4NQgU5k4AYcHr+4iWyrg1V3VLlmJ3uh8Jdy/Neb6bzZ6bNUYqMCK1jJfuT7Emzridc/vL+l8cKqHrVoTAHpiGvv0JL45vvMAvmpnXzAqnHnbfwEm3e96C6eKEwjASFljuGqRdGFLuWYTBBaNdUa/IpFL47O7cNscBJ0+Gt2BuiKG2+ZkabiTZQ2dtPkiOFQdXdVp9TZUR4OOvVdJgohU3VdWN88OjmaLJqbPxZqffpPI1VfQ/5Vv0fuxz2NWYy9DVhhdvo6MP8hU5yzdd+KIWHGmkGNWE9S+ydnj/NPOBNuHZvdlpy1ftWQrMjY+zMgvf4dy7sksqSbreZe3jvFgShKZQLjW/TRNE9M0MUyDVD6DR3eyKNDKsoYOWj0NNL35RuTmCEt+9WWkapxmmNY9mijlrJn8I2jviiRTNivkSoXnFHceig4xnJikWJp/fw/FcvPGAHaOTJOr3i/D0/XPTxes50qiiIl5VMummQRVKheJ/+kW+hefSlmzI2DSU7HeNOs7/sKuVfzQefnJHdzyltMRjwiR1jQ3sLZ5yXOe1f1HwYkO6rNEk9dGb5WzX9DdDC7aRNfuP/PEOTfS4mtmMDZCtpjHqdnJuzzYUgkW3/9H+k46k7zHjyarFMpl0sUcE+np2vxWd6CFBw9vQQAMw2BT+8oahXIsEZunwgiwuEo12ldwUExWGI5ZN7Yqwek9tlqnFyCdF3moN82GikZAKuGVSgyUdXJFk32jRVa2aHznvhhf8FiUQ8MEuVLBLSkYcxZYWZLJlgpkitnnjeY700Ht2L+Zsqwy1GXRVHvUDAgCY+L8zwk4RDxHzD04NTs2WSN6DEnydCFDuVKm1duA3+4+rq7okfScvybag/Xfx35EB1USRDRZw67Yah1VTVZp9TTMo4zL0myC6rE5WdW46DmJPFmfZ22mmqSgyQobOw00pcQPHqpfoB02EUEUKSsqcrFIZN92xHKZsqrV7DZ2Fp5dghrPpcA0CTq8NZ/aY76+Kl5hmAYOxUaxXMIpWoq4Hb6mo75OEkSQFcrVjy9USmiSUpsDnQtREFnXvIQnzilw0cfeRkg00V2zx5X1+vEP9Nb+Hz64e957ZL1+TFkml0+jqzYQBHy6G01WjqtTDKDLKqZpEHb+5ZLyjlCIRS94ATt+/GM2fvAjtb/nShWyHi95RUHPZvCM9JNo7gDAJitMZ3MLqoD/M2EilWQgmsduqxCdU/X22K0ZbnmBBCw4so+zb/0ckiLS8o5rMSQJLRsHLCXGmVktsBQqJxavJOrxQTaGx+aoFR/mwq7M3p9zKb4e3cnpnWtRFm1k6wsvZPQHv2H60hcQWbGilqCqGev+OHKQvX/K2hd6lCwrhWmGdh3k6j8+SHwqxuqXv5gtV7+Zi8q7cVQVh7PeAENrNmFIMnffWu8HW0Hg+tE1OCWDV51qHV+6mMVjF5hcoIHb6rOTKao1Yb28x0/vGRfPf+IcmKZZpeIb9C89g/vM93L6HV/ixTf/C4eWn83j576WcnXdjitOErmZGfsyDtWNqDsxAf/gIcK2pVTs3joP5EwxXxUcUylUSogIz0hPH9g7Tlv15/hItKfOHiieqRCa478KEF6ADSWUy4iVMhXNhixK5I1CzWP8eJAt5muz8AtBk2fYWda9eHh6hP7pUQzTEgB025wEHT7ApH96lEPTQyiSxOJQ+zHHJf7aGE3Mrh0Rj9WBLFaKqLJCsG8/ejJORYKZXP7JvIf7cwE0pYV15iRyoUDb05sBK4HK+axuXq4a/2y651tEhnax9fK38lV9BHFCoAI8lvPW5gDPdcRgTn1nbtKQLuYIOXx4bE4CkrzgPtriDddE61yaA4d6bB/quZjZx4MOL167HbBupHLFtLrxgsniT3wAyeVk+Ls/IXvQ6qR61q8h0dRGNNLKwfESrQUDhyYyecS8edaoznaWrGvtaN/LpoBNNSwhzHKZnd+9mUo6Q+srX4qnOj6Qd8+Kh+VKBaKZOI3uYK2jP5aKVtk0AWyKhk93185LPJeiIdSE8rEPsOPGt9Cz4y72rr+MiiFY2gvxCTYIAoJhIFQq+AYP4R3pp3/DGahVR4lkPs14ehq7YqPV2zDvWCqGwa7x3lpxaC4S+TSJfAqbHKqd4xlEM0XiRwgaDU7nifgtJf3DUyVa5Rw2weBAyTGH4jtjNXPsBLX1wGOUk0kOrzoXgKVqBo9YomSrH2E6Fiy7omKt6LG6ReQjV67kg7/bCYBLk3nN6V347Ufv1v+z4UQH9VniSPuBgyvPR88maDn8FA7Zja5oZKuVobkV4hmlNVVSLIGL6jzJ4nA7Xt1lDeGnY+weO8R0NslUJl57be9UnIXq0z1Skl33Pc6u7/+Ug1++mdDwHjBNljZpaIqIRxcRBeuVmQLosmB5GgJesYwmVFiuptgzXOAnj6a4TB6iTZ7dLEoVk83b6ktHuqKRLxVIFRaed/pLkMyVwDRo37eZ/MpNvPgMB147vKClhAB4WwJIR6ypTT6lZpA9A4eqY5M1cqXCUUUxZuxYgg4vSxs6nrdjeL5w5dpmmr1WYcKhSpzaNXuMsighSZZCmzXbYcNWVRleqHNm0ZDEKjVVe84KxNZGKtPqi+DVXaiSikO1ceoiD5pcf74dmvWDzQRs3uF+wNrgxpauJtnQjNDdcczP045IUGPZJEGnn05/83HRWDVZrRlW++xuPLqTsMvP6Z1ramqWC0ESxaqIibXpFEpWULhQgjoDu+5g33nnobnr37foeGaqTd5tBbMzSsEBuwe/3Y1D1Y/bd3dt8xJWNy4mcAz10ePB6htuIDU8zOQjD9X+lisaSKLM3kZLMTSybzueEYteZJM1CtWRhb8W8qXiX82zsVQps3d8iDf/aID/uVvmyUMq05nZQMWpWTOjulq/VYaG93DZz99Hg5ij5bMfwQh6aPc31axkCk5Xna9tJhAm3txBShKxK1ZnfKFA0aHNFUma30kAOOMzn0LUdQ699T/Ij4xhKCplTUOsVFByWTBNS+il6jExEC1xhTbEew58j199+Kvcd/OvySXTnPu6q9my4mIeOlypEznJef0YisqesRIHJ+ZT+AfLOkrYT8RjfZ9MIVc3hzoDt03Eb7cKLc9GkCeeS5Er5pAlay/qW3Ymt7z6SxxeeiY92+/i8h+8E9+EZasR8cyer3S+jF2xYc6555piUcrGrOhLspAhW8rTHWylweWnUC5aXcln0IMY7bWS928nWjhUqi8ixrLGbAe1uDB7R6iU6XjyAbo3341cyNUUQEvPJkEt5SmUS0cVcFIki/iaLxUolkukCznSxSytvgZEQUAUBGyKtRcEnV5KVQG558tj8i9BsWzUgnhBgLBLs5SUy2W8ZYNA3wEAhjaczqGWJfzZ0cO34hadt1CBnLu+EKBmU9X3NcmXTFoPPMbyp29j58YrWXzyqto9Nyk5eCDnZ6TaQXUl6+OcGcpqoVxEMK3i98bW5axrXvKM+2ijO/isivcOVafd38iKSDdrmjprfy9VQBat4o4ginS/7x10f/DdpHbvZeu1r2XLda9j4vY/8e374nzqtmk+fkuUcqVeEO2tF3hrHdS1YhSzXCZ9lFpi0AWaYo3EZAs59n37e8jLumnatKlmhTYzfwrQOzVIKp9lPG2du4phMJ1JYFdsTKSm0asjKjPw6i7O7lrPZa94PcWuFSx/6lYwDQxDZCQxiVd319ZM99ggoUN7ULMZHNOT6IpGupBl++gB9k/0s2P0AL3RIaKZRN3eMJqcZDQxxYGpWWVtsFhQ2WKesmGQLSyc9uwarR/FODiRZmufzGtvniCZq/Df4T3cHNnBcjVFJm9gmmbtPl6Iqm8YZm0GdfH2P6E2RTj92qU4hDKXOieRxOpozzEKGTO+18OJCaYycXTV0kKZYXJdd1IrV6xpotFj4/PXriHs/t+TnMKJDuqzQjI/S/2awVDXBnJ2Dz3b70KV3oBN1kgUrK7odFs3tmQMx/QUzqlxxk3TUiSrFEkVskiSWBXLsJKqTCmHy+YgVcwSyyZp9zVSKBcZjs8mgw5NIFMw0dMxbD/9LI8P9FP2BpB3PM1lwFRkEcrpZ1JYczVKJITTZpLMVb1Q8yKxqn2HRyxxo2eYl7tG+PZggt+lG7g+bC00j+W9KILBei3Jlj1xWroCtPitTdFWTVDThecvIE3kSgRHD+BIR4medBbrWkqcvdTHsl29MA16g48vviLMu382wYxd6hWru+clGbqi4bJZVjAzPmOZYq46G6wTsHtIF3K0uMNsbF3+Dynq0uzVue/d57B/PEXYpdUtOIIg4NfdNYGisNOHT3dhGMYxqZ0zdODnCkWU0RUbiiwTsHuIZuJIokjEFaA1kOLg+Oy94dCsBTTv9tY2N4B4cyfpUIR4SycvNk12jaU4NLHwdxtPjeGx+3DbnORLBfKlAh6b47gFntw2Bz7dhV3VafE00B1omScXvxAkUapuPNZzc+UCXpvzmN32Gc+xPd1LWd67j1RDEwWHm6LjmQOVmXGAfKmIT3cRdvpxaXYqhnHM2aW50GT1ebmel1xxBarLxZ6f/Bi58RrKhknZMDFNkWGvl3a68A8conH3FiqKSirYYG36xfxfZJ/1TEgXsjw+sAtJFFkZ6T6uzvmzwYHJAX7w6GFL1Rb4826VZZE5Pnw2S1Btxm/4AvsUyvQ4nt98ArfbziXveCXZJW0kwx0o2QxaOoUhyRScHhBFMoEwjugE022W922+VERTlKP6ENdRq0sL0z+bFy1myVc+yZ7Xv4ttr3gj6375XfIuL87COJ2P3QfMCo2UbDqOvdD5p8/zyHiUUEczZ95wBY2LOxAlkafHPcQrFbLeQK2IlA40kCsafOO+oycuXrt1f5umSbqYY3HEz76x+j3hHRe1WDZdklLnu3gslCplJtLTtHkb8Dujtb+nfI08fMnb6V15Lmff8hmu+N6/sm/dC9He+BZmZGIMwxKKy3kD9AeCdESj6MUiZcOoqc+n81mKlTI2WUUUBIrlIggCDUfcO0KlQqh3NzmPn0nFxTUui1m00FjCjsECa0KzFN+FEDy8Hy1tJU+OqQkSobAV2D4bim8xR6FcxGNzsmekgEeXaPLJiKUSYqVM2abXCuCxXIpcKY8JdUq/Mwg4vJjAVCbBoelhAg7PvPEFgL1jSb5870HOWBTkZZva5j3+XDGRytdYuSGnhiJZ1mDFSom2WBTBMIiHGkkpOuKSHgb7ShT3WtdlsWySd3trnX+waO4JIJWrcNL2W1ly7w+JBdt58pwbeYNzLwKQCjdyS7EDE4O+0sL3Yc5rMVESuTQum+Ur/ddSRRUEgaXhjtr/NVmkULbWI0mQiWVT2BWdRD5N8OVX0XjNlYz+4ncMf/9n7Hn7++jU3TTqbg6uuoD9G19JLDN7TXWGFPZWO6hNUp6J/XsxzIUppT6HgcfmJFfMc+CuP5E71I/vQ/+KIojoVSXyuQkqgEd31Aq5yXwal2bHpmiki5bljvOIdU4QBFRZoXzZK/B86T9oOfQUxqaTcap2WnwNpAOTaOkkjXu21V6j5jJ4/QHGk1ECTi9TmTiSKOFITLBvoo8GV4CNrcsByBTzJPJpwoqfyXSMoMNLxTQYSU6SK1sWe6P5hWOABw721v1/LGGQGNUBkxY5T0iyks33+A9z49gq8oUKIoIlkmTOv48TuRJlw8QZH6O5bwuBN99IpFHhzYt2IJeLCAgkIy0LfheLJm3SPz2CV3ehSQoT6Rh+uxuXNrsGKZLIl162bsH3+N+AEwnqs8DwQl5JkszetZewbvNPiT65FX25n/G0tbFWVI3Bdaex6KE7UfI5SyzF6cau6oylooQcVmBqV2xMpqapmAbdgRb2TfSTyKetilQ2Sd/U7ExqR1BhcPshLv7lTZRyMc55zVW8r/HlLA0aDP3xz/RsvwvPr7/LE3f8guZ3vRGv42yS1a89Goe4bm1WPqnES10jALzOM8TrPLOzKB+eWsRbff2gQUgqsGekWEtQdVkjmUszmppCVzTafJHnfF6T+RKLt99FWdaonHQK+VIeOyL2eBRTEMh5AzhVkdedAwfHZNa0NPHKUzsWfK+gw4vH5iRZFbwYmB4l4g4ykZ5mLDmFKis4NP0fMjmdgSqLrGxeuBO2uqkH0zQRBAGv7sKp6pSNyjMkTzqq9NyP16u7WBRswaO78NvdTGeTmKZJwOHhVacafPB3s4qCIVeV8rN0Ne6xITyjQxQcrjqT8XypQMglcGj+aBkANkVkODGJrtjomx6hweW3xBaOMwlyanZO71yLLEq14ELgmYMMSRARBQHTtKqk+VIRm1PDqR1dPU+r0onHfD6k8y6vq4qWbDpKPsdk91K0dAr3+DAFp7vWbZvpAuTLBTQ5gEuz11kS/C2h6DrLr76a3b/8Ja63vYhYdYsoGyIlo8JEz0pAwD/Qi2d0gHQoYnXIKqWql/Lzp+6dLmQ5FB0mlk2SLxcIO/3Pa4JqmAbRbIKhWArmCFzEsrOFFrtmUiqXcOsSYSHN1Tt+yo67NpM0DC580yuxe1yUq8mXa8JaT9OhhtpM1vDKDciFPMUqDbdQLlaLJgsXHuZSfOfOoM6FS3PQeMrJjP7X+4i99SM8+Zo34/ncB3FOjdcpYKamE+x75AHOvv1BDK+LC//lZfR3bSQplmiWrCLqgZKdUskg3tBCzuNDNAwKTjd3PJWqJe0um8DyZo3HemdbL25drB2PJIqsb3dx69bZ/fE/Lg3xipOX1YSHUtljM24M02AoPkG6kEWtzl/PrCFzMda2mt++7uuse/BHLH/6NorfSSKc+W5MUcIwZDp8jfRODXHAH6AjGsVWLFAxKvTFRjFNk1Qhg1PTEQQBRVJqtivKEUlcqHc3/oFDwCF8gvVYwRTZvcBYwt27slywzEYPIJeKYBhwBGXWNTla+7czOo4UbqRiWBY4z4R0ocz3Nh9mc+8IDd4KdsXgx48kkSX40JV+zjrwEGo2Q/+G06sF8BKT6ZglFniMfc5v9xDLJplMx5hMx3FqOr3RIRYFWmvX50dv283DB6Pcvn2Uta1eljW6SRWyxHNJWjzzKZbPFmNz6L2NVeZQrtoBrjyxld//+FbGDg+DYSA5HBj+AC/OmuxffSHFtmuJN7XXuqwAWjpJOZWm/90fYeU99xHu6eDm8/6dy5YqLC+lMSSZkeXrWV8W+emuSXqLdjaHVrDaVaCk20kHGzAFAUNWqh62Cbr8zTR5QvO++18LcxNUh+oinp9kz/ghnJqdyfQ0i0PttLz6ZTS/8qXs/fGtPPD7J3HHhtl4//cY3XcXxlUfB1cQUQCvQ0Sas6Y0DR9EIkBlgX0w4Crj0vwkcimGf/AzpICPhksvJHh4H1KxSNHuqDEtCuWiZZUla+TKFmNtKhMn4grU6K42Ra0p5R8J6YyLyHzncyx/4vfYbziXRrfKklA7/dEJAv0H6p6rZDM4VB0Dk6HYONlSHkkQyRVzHJ4eQVdsVAwDSRSr4qM5ypUyO0YP0uINM5mOkcynSeUzVvKcX5iOOzBdH98nsiqxjPXcpXPsjbqVLJ8K7mPtQ4+TsdnYuXbTghTf8ZT1fj3b78IURPRLz8NnglK1CCvaHbXi9Fwk8xmG4uNVKz2dRk8IRZRrDK7jHfv534ATCeqzwEJeSQA7T76KxdvvZNdHPshJv7kZQRCqals6CAIZXwjP2BB6bIqC0z1PJdCu2mjyhC2JctHyY8wW8zzav4NCucjg9GyCuiRxgA0/fi8OyeCCt99AtLGH4XEbalnm8LpL2LfuEt64LIP+zc8z8J+fZ/XZ+xk4+fUgCGSLkNBmOqhlcqaEU6gPghKGTMaUmahK+IflIslihY7H7sOQFfrWn0a2lKcvOoLH5jzuBHXzwSn2jqW4emMLblt9MBCfmKR71330Lj+bkMeBKJYIjg4iGCYZf5CKqlndJC3DtSd3cnrHElR5YZpG0OHFpdkZSkwgSzIuzYHP7satOSylzlLun16Cu5ZsCQKb2lbWWSgsBF3RnhfT5hnBqBnMVYq7ZkMn/3PfIUYTJRrcAlest5EuZMHtI+/2MbFohZW0CQKliiVIkSsVjkmXavZ6GUtNMJGexqe76fA3szi0sCn70fCXdPQEQah1UctGhYpRwaYcm+KrVtWey5XKPMrOwPrTcU6NEWvpRDAN8i4PyUgzejKOUKlQ0WxUjAqGYRyXsvRfG6tvuIGt3/0uHb1PEOuwFAdNU0YAKqbBdFsX/oFeHNEJhErZUlmslMiXizyf2oHbRvZbyovFXI2O+Hwilc+SLubqxFEAbtsyGzTLUoHpXI5VETv22z7OYzu30bColY7LrsTT4EUUQcumkYqFWmCVbJitihuKSnEOfTRfnSE8egf1mRNUoWpeH9iwDt9nbuLQO27i4U99hdClpzHVP8rg7l6G9g8QHx4HoG31Ek575ZV8wVxH64oW3Ls3WyplJhSq9L9k3sBb9X00TbPOUue6k93Es2Uem9NgcNms9TdbKmCXbaxuCgCzlaYrVq+whL6qHdRnsjQZS0XBNFkcaqvNM0fcClDPWOoMyhTKXp646I0420O0/fa7nD+R46mzX0W5eQnNnjCD8XFyirXeaYUCuWKeRC5FPxDPp2sCIqIg0BNqq/27evCEevdUk1MLWqVIzJB5x8QyMqa1nly1wcm9e7LEswYVE+7dl+VkuxM1m2bpvbcyvGojqQZrrZTzOdTMrFewIzqBVl1XUoUs46koDUeMq8zFZ+/Yy/cfsbrbkqgii1awfLoa5ZwnH615SjbteprB1RvIl4tMZePWaMIxqMuiINSS1LHUFLnpAolcmlK5zIZWy/v34YOzXeyfPj7ABy9bylODuymUS9hk7S+yK5uLufOnjVW2UL5cJHX3/dzzsa/j8Lloe+31yAE/ub4BpsYS5Hon2HTfd8gcfICB2EvhojMJjg7gHhlgcvOTPPmOT1EYHWfD5eey6sLTWC4maPaWEKcEUoEGTFnGKcPnrguRyhlEvI0sVCOdysRxqVax8G8pOmNTpBpTr8vfzmRWIlXIEHT6eODAMD/fPMnyZp3OkMJtrjM4fLGlVNh0eAvn/f4TXPSLm/jDyz+NHnAhCgKjkpOCKaIJBuUKnKLHeDg3vwC6OFId4RoYIfbnh3HdeA1Opxv3nu0AjC1dU9vbUoUsDkVHkWSShQypQgZJEHDZHORLBQQEy5f9KIU4m83Gk+suYcODP8SfKrGhdQ1Bh5cD/jC9gSCLYjGyviCO6UnUbBpBEOgKNBPLJum0N3N4epixlMX4mymO6oqNVCFDrlSoMiZKjCSnGE9GiWYT2FUbja4ApXxmwe80NJ0HZtffmeQUYJmaZs4SwWl6HNMERz6HkrVU7Btc/joWws6RUQSjQs+Ou4gv20je5yBQmF3PRlZuqIsVcqUCmUK21ryazMRo9TawJNROxBVgJDlJqpB9RmHP/004kaA+CwzHFq4Cl1Wdp85+NWfd/l/k73yAwOkrGYyP49LsRFwBct4AnrEh7PFp4q0LexTOpavqika2mKdiGgzHJxiOabiFIqv33IPnjpuxuRxc+ubrcIf8fC1qCfgcnpq98IM9rXR//6s8fdNH4ae30KN3cmCN5aEVN6yNe7GWxacYgEC5YtZoNlvDS2HY8pUDSyk4m0hiq1jdHrVYYFHQsp45Xh+1gWiWG77zOBXDZCiW46bLl9c9nr3tlyjlAns2XE6TVKYpXyB80DKnTkaseZNcKY9NteG1OY/Z/XRpDuyqJYgznU3Q7A5btioIbBnei4Fx1EXznxGqrCwobz6DRleQ0dTUPMGA5xs2ReJ/XrGE23buJeDOEsuNkCyINLpDVsVvxiC8UmL/RD82RcMmq7h1mSOD0Bk4VRXDNEnkUiwJdbA03PG8U0iPBkm0uqiZYg6brOJU7cfsFqhVoYuFZspKdgextm4ATESmO3oASNlmCyXZUh6bouHSjv05fwt0nH027pYWWrfdzZZqgmoYErIkU6pUkGz2GnXbHouiqvKC6uPPBdlinkwxTzQTJ1PMY5gGmWIOwzQWpCL+JYjlkqQLGSqGwlyHxTkaSTR5nYScEqM3fY7Kzm2cds1FrDxvE4IgYJgmoiCgZtJ4h/uQSiUy/lAdS2AuLLuicm2GfCHMtZnJFY8+nxh2+gg7AyiXvRBjIkrfJ/6bH97/GACibsOzYS1Lr3wBqxscOAJ+vploZdAV4LoenYq2DHX/E/whP1tcjGUMvHbrs6fSFZJV4SG7KrCpS+F3W6PMDRc81Q5qrup16Lc7+PiLV/KFuw7wkg3NNHqsKr+uaNgUlXLF8lc0DMMqZMzpAuRKBZK5NEtC7XT4m0gVs7g1R9WLtv4cnL86Q8QjYldsGMbV9Psh/KNfcMmP38tu3+dRpAvRFQ1RUSkrCnKphFoqMZaKois2ssUcrd7Z4z5yL/EP9BLoO4ApCKQamnCMDpOqiHw42sOBkvWdVVngrKU6jV6Jr95j0U03H8yTWR9AzVqJaPOOJ9nb0My+0SJDTx2mQzXJhxsQDBPH9CRLH76bzNKVDMUnCDq8x0xQ798/Xvt3xRCoGCZg8jZf/1zRWsuLtWIwXrHsNCbTMVr9s8cqlks07NuBWCkzsWgFJbsDr+5kPBVlKh1HkiRrzq16bSbz9fv7zuEEg/FxopkExUqZ6WzyL05Q79kzzqfv2Mv+8dnEvdVvFW2m9u5h6sP/Tai9kXM/+BbGzrqw9hxjtMg3b5tm0Y57WL/1d+z/wMc5+AkdUZYxMlmMSgVPJMgL3vNq/G1WgaBbTCFPWZ+TbJgVx5OlMsnSKErGO2923zBNopk4i4KtdPqb+VvCNqfj6bP78TslkoUMbs3B+7ZOMBI3ODQ5P8ka6VzHPS/+ABf+8kOcc8tn2PX6mzBNk6QscOnQRl7kGuct3n5e4R7h4ZwP5nRRg06BZp+KIAgUfnYbSCLK5edhl2TUfBYEi/ZsmiZDiQmSuTSLgq3WmmZUmM4m8du9dPgaORQdxmd34dFdR12rNUXk4KrzWffQj8n94dcEr78AAFmW2d7cQn71KdgqFXoevBM1Zx2rJEoEq9dbsydMLJdEV2xVDYQ8xUqZTMHaIwrlEvFcEpdmJ5pN0OptRZEkGsb7eW96G+O2pTyR92JTTPIl6zxE0wt+VRQMTtdjKJLAPfYeNiUOogmGJSQqQD4ZYzA+TjyX4uT2VZZ+hWlwcHKK5kNP4UhPM1EVhnPnrYLMVOfimvaEaZpMZuJMZ+JoskqjK4hHdzKZieFU7QQdXgRB+KvHcP+IOJGgPgucsyTM520Kw/Ec5YpB71SGe/aMky8Z9K44h2VP38rTH/s0J9/1K0SnSDKfYTqbRK+qytljUwvSf46EXbG6T8lCBkVWmYqVeP0fPkJq+3Y8S7q55MYrsDkdvHdyCY/kvfNe77WLpApZ7P9yPZndQ2y699sMLtpE3uElXhVJ2mhP1ZYnRbKCrV2da2nuaoct44xVrE2qVc6TzE1DdR+3JeMUAmEqlQrl4xQu+daDh6qbKnzn4cN1CWqlVEL4488YbV1JLNwJQpHWpLXpJxpbSFT9zTLFPA7F9oziA5Io4tLslv1FqYBT0/HpbiRRRJZkfLr7uOf6/jdgcaiNrsDxiQo9V7T6Paxt0+mPxekONJMq5KpqmUotEEwXcjhVnXTRknU/b3mI+/em53WL/uf6dWiyZWliU2347EenRf41IIkSYpUypB+HVYAqqciiPE8sYTw1TTKfpsPfdMzfIJXP4tLs+O3PTeTo+YAgiqy6/noSn/0ctkyMvMNHuSKiiDIlo4QNlYw/aCWo8SmUxmbLp6783I3UZ5DIp8kW80SzCXTF8rLMl4rkSoWjdh+fLaazCdKFHPmixtGKJGG3jdg3vsfEb29n4+Vns+r8WV+lssOJms2g5jLoCUvtNtHUdlTRi2PZFc2g3gf16POJYaefFZEu/HYP9je8juyiZrR9A7i7OvGfeSqiqtA/nMKxw7JA+22qgbUN1mdKbU0cCpzHrQ8Wascdy1ToDFl7Q9+cYmfEa7Jvsq/aQZrNhty1BLWAX3fh1Oxcf3ID159cz3AQBRGf7sap6iTzaUYSk0iCiBJoRlc0KkaFkcQkIYePVl+kxtBI5tP47U5gtpPrd5j0hJzIosRoaoomd4jG197I59WzuPRH72Hx9z9K4cPXY5Mt4bi8ZsNZKtFj9/JEbpqh+Bge3XVMxVrP6ADFfIE9poPRpw/xp3sPIyVjeNN/4PJMDKW9ne5XvQSPHqYzXEKTTQplgUQWpnQfPvpr75XIVvjUbdN8LjSOIcOQLYitMYBjehLBMOiKTjEWaTimAFi+VGFgerbLeK1rlHPsUbYX3LWZuKIoI6gKSj6HL5+jzyyyLzPG4XEf6ZzAptYSjbu31ijoACXdzkTPSiRRwmWz2EUe3RqNMQljmiYD0fqC/NbBOH3To8RySQzM5ySu9NrvPznvb2cvDlsqrB/4OJKqcNEbriHXUu9vapOte+vgqvPJnXkB7wr3Mn3/wyAIKAJ0iAW61y1FkCWGixoRaXZNije3kwrPJqgjiUlssspocnJegpovFVAlGY/uPKag3l8DNmX2+syXKixrtL5zqVJmJH5sm5XR9jU8esEbOf3OryDc8yP6zn8lbh0OI3JrOswN7mFWqGk6lRyH54h9NfkqOBWd8Zt/SPZ3f8L90ssRgl60fB5MKOp2TFEiV8yTLxVYEm4n7PIzkZomXyogCSIdviaaPWGimQSKJLPkGGwnTRbJuoIM9JxC66++x/R/vht/dzeyaFnZVUzLusmQZKRSCVsiRn4OHdZnd+OzuxlLRilWSuyZOIxNVkkVsjx5SOHxSoa1HXm8eoZkzsa7/jiNKMB9Ldspm/CfwQO8cOgkmn0KvRPW/RfPzl8XztajnKzHaVYKFBxuxKWLeMVvHWy0JTjHMc2ZjgRBWWXH1AAd/iZiuSQBu4eRxCST8QyrH/0VWYeX3NoN+OxO1BGL6j+j3GuYBv3TowhAd6AVRZbx6S5iuRRumwNb1c7v/ypOqPg+C3QEHbxkQwtvO7+Hd160hK++fD0vWV+lcwkij5/3OnJjY0x96mu0eMJ4quIuRbuTot2BXCzgGXtm3zG7aiWomWIOt+TnjF99itT27Wx80Xlc+/brcHudHAp2UmiIwBGzBIIA2XKU4fg4YVeAng99FLlcYN1DPwIsCi9zXjWjNCwKAo6IH1EUuHydgz0FS6p/qZamtRCz/KkAWypRE5ApVkpH9X+aixkbmYXw6Ne/hjw1ys6TX1L9SwFfNUGNtXTWgr1MMYtdtR0X1calObErGrqi4bY5awHJuqYlLAq2Picrjn82WLNWf5sFzqXZcag6nf5mdFWvzntkOTA5WFNVLpZL2FUdSZAolkuEnDbufudZde+zqcPPJaua0BRLhddVLTL8LSEJIiICyXwGu6I9c4Iqy8iSSMWo1I7VME0m09PossZEevqYr08VMrg0xz9EggoWzVcwKnTueRCATMG6jmZ8G2dsGOyxKEpVBOf57KDGskkyxRxhp5/OQJPlb1x+fsTZ+qYy3LptiPFUqkqrsviunwru5WsNO5HmJGLK3bcx8JVv03rZBay/5My695nsXkbJpiMYBs4pq8uVd83+fjPCXmBVybOlwlHtimZQ7z979ARVEASaPCFsiorH5sSzZgXul19J8PyzEFWF3okiH/pDhrdOLOe1Y6vImHKtQwpWgOSyzzIvpucIq/RPza7XDe4KkiAS8dRf/27dutaLpSI2xXbMGXi/3Y3L5mAkMYlPd+G2OWs03sH4OLqiEnb5aZvT2XTbnKxsXMTpi2bX6ivXK3h1F36HG6dqx6nZcesKGXeI+y9/N/r0KH/+8IexKSqapJJTraKYks/S4W9CU7R5yu8AVG0tKoODPPaNn/G9d36WR9/xIfr/8zP0PPxrmnqfwp6Jkbd78O99gqk3v5ndb3kvyYmROvXiB3Ml8upsZ/yhHQmWqmlOsiUomCJbpQh5j5/xJasAUAt5KsbCCqBgXTOv+/4TVGu7SJi8xdvPSjXNy6v6EV+KtfOzjvNrYiuuVJIWXwPb+3zcuqXAV+6Ooz/2eF1yCtTm3wF8uovpXJKR5CQV0yBfKhLLZnjRVx+uP00mRNOWd2zFsBgNf8k9v5DCvssmc3KXn71/uoPEo0+y6rKzcXhdZPz1XaOZwghAPGfgP/s0Ft30HhZ98N20f+DdyO/4V6aXr+HnjrV8N2EVOwRgcO0pjC1bW4snKkaFXDFPkzuEJIjzigTZkuU3uZAV1F8bczuoh6cyfO7OfWzunTrufXz/movZu/aFNN3za6Lf+BEBu/W6nCmxpepjvFit78CG9ArRf/l39n7yi/jWLEN+3dX47O4aI6Bkt+7/ZN7q5DZ7LGbazIiOS3PU9CHWNi/hlPZVxywoa7L1usfP/39UEPj+9a9mz2ii5vVeMa1RmXiTRcFv3LNlwfdRZYVcqcBQbJxcKc+W/jx/3q3xwD548rDMZCbOb5+QqqrOBuWKde05hAr/07CTZs/c9bY+lj7JFuejwQNc5phEEKz1vtGnUrLp3J4JM1TSME0Tr6jQ4AqQymeYTMfYN9nPvol+Sr/+OQ3Du3nynBtRbCZuzV7zgp+xBkvmMwiCwKJgKxtal3FO9wbWNC22fhOHD/0Ye8X/BfzfTc2fJ4zPMZmeaFmB+9VvZed3v0Tk5E3oF2xkIjMNgkC0vYfGPVuJ7N1GWbMd06Rck1VafREUSWbnf36V1oOPc8o1L2D5ORsRq8686rIumnbD0/31XQuXzSRTyLI41I4qK3Sf28Pv1l3C0qdvZ+/6y4hHZoMAQ5YZW7Kati2bEQyDYnUG6bI1dkqVHIcm7HQrWU7XY5QrIIkmejyKIAjINaPx8jMKDqXyCyeoxXSaBz/6UWKdKxnq2ghAl11Bm8xgyHJNMa5QLlIolXAfxTvwSAQdHgJ2b01VbgZ/j2ro/yVossra5iVUjAoOVefhw9tw2ezkigVKhjWrmCvlCTq8aLKMWZXvb/LWB7czDSgRAVVScGtOfPa/bYIqCiKiKGGUSzhU/Rk796JgKXKLCFSMCrIkky5ksas6Da4AB6cGaHSH5s07grVJSYKI2+aou17/ngivWEGlcyndu+5jz8YrSOVNIna5FsjlPH5MQUBPxvClUoxTJvc8dVDThSwjyUmS+TTdwVZEQUST1Nqs0XPBl+85wBfu3o9hwpo2mRdt1EjmDM7QY5ymxwFolvMMlHXa9j9C8pbPEjplPee9+ByEUoFo+yI8Y0NkvX5S4Sbc48MoeStpNiSJot2JUR3NyJbymIZJZ7CZeC5VU5U81oyxY04H9c/7JoAVz3hMLs2OrthIV2d0x+JlPnWbVRDZVpi9b2aUd2fgm5Nc3b4txeKmFC3eBvomZ9frrrBKo9tNpmADZjlw+XKcPeMJ3DYHfrv7mLPkIacPn+4mXyrS4PITryZDiXyKimGwKNDC+pZlqEfMyTe4/LzvkuV85o59rGlxsbbTWs9bvA24NSd+u5veKWt6cLx1JYfWvQDxi1+k9bqXoNkU0qpKCFCzaZyRFiuJrlrvuMeGUPI50sEGvI88wJ7f/ondf34Co1Jh0UVnYrv2GvZpLXxzq4g559hufoWXoe//lP4vfhMef4rWl7+fUafFCCoKTm7r6eGywUFsyQRvTzxApcr2/mMmxGhOZC2Q8VuCO2ohT9moHLWDev/+SR6aMwO6Upv1bowZMl+Lt3NHJsTVyTK5Ji8AeiKGa9FyHjtk/VbL1BQNqUlMuV4ebm6C6lB1PPpMR8ckW8zz3/ccoGzMTyR7p8ZpDbirjAlrPvyZLHqOxHRmflK7qcOPLAo88OEPo4QDrD1tNYYsk5vjJVwoF3HZZkPWbAF6p4Zp8zXUkreS7mC6fRFb+hKkZ9YjYfaczyBTzGFXdWRJxqHqZIq5uuJ3tpjHrR1fvPF8wybPXm/v/uU2ssUKNz90mHvfffbxvYEg8MhFb2KpXyTznV/SfHAa4eS3YYoSB4t2ztGnuaCxyJ0Hq883DTq/9yVGH3mK0665iGUvOIOdLYtQZRXHfstjcyY2TBbStHoaiLgC1p5X1V5waDo+u3X+JFFEeobe10yXOOMO8eS5r+G0O7/K215zE93XX8OpS6ziF8Bkz3K8owNo6RRyPkfZVs+ecao6Y8kpawRkIsefdsyurZv3a1yyRmA8YV3HTXIBk9nmzEo1zTJXkQeO8h1f4hyr+//M6EZnSGE6UyBWUTAAuVjAbXNwODrMSMJSlN79yIP4fvtD+hafRu+K8+hSC7izWZR8jrKm1ex00oUsbs1Ou7+xTtNjZaSbQ9HhOnXn/4s40UF9jnjBysa6/2vXv5nuiy/m3ne+i8L23ZTKZSqGQaKxlXQogmAY+PsP4pwYoXHXUzTufprGnU+h5OorWk7NzsT3fk76Jz9G2HQmy87eiCBAWVVJNLVSdLhoC8yfPVzbptLgCtDoDnJG51oaPQ62nP5ySpqdTfd8i1hFJm9aP/vIig2U7A4On3wOh049r0Y9jufjbOjKc8CcXZwfzXvJVUQc01NoqQSyZNEZi8dB800dYc2za6yX7aMHuOVD76cwOcW2C15Zy0pWV6zzkPGHoMrlH0lM4rO7aHAFjquK6LO7WRxuI+IOLFwxP4G/Gvx2NyGnD13RUGQZv91T80E0TJNcqVAVTrH8+BbqvMwkcc7qDLfb5vibilSA5ZfoVHWWNXTi1V3HJVykSAqyJLN3oo9iuUQyn8at2VFkGVmSGY6PWx7IQDSTIJFPW/Mn6Rghp29B4/G/J2wXXElo7ACe6CDJnIkiybXvb8gK0+2LwIS2g7soVcqk8hn2TvRZ1ePn4FvaHxtlMh3Ha3fXkha1eg3ljmLjcTy4ZdsIn79rf60jtWuojE3RSeQMrnfPdpjapAxrH/wx5/32E7gWd3PZdRdgKxUwJIlYSycHz7iIkZUbQRDIzw2gnR4QBCbTMUwswR+f3U00m2AyHSPg8D6jn+5ckaS+aJY7do4d9bkzcNkc6IpWS97/sD3DQg41qlx/bS1tnE0sYhnYNVgmXchweI5q/NKIE6/dxYqG+jm8bDlB0OHFp7ufkZGiySrrmpewPNJJu68RXdFqLIoWT5gOf9NRuy0rmjx8/zWbeOdFy9jUtoLVTT00uoNsaF1GZ6C5ziv5sdNfgepw8PR/fgJNVklWhZKU7OzeGjy0l6X33ELTrqcJHthN7rOf5zfv+AQ7736U7g3Lufajb6X7o+/Hf9apjMu+uuR0RbOKYNPg2hcQ+d7nULweln3rJoIjlnq5LFr7ZanKtjBNMIA/ZEJ8KdZOND1r/QOgVNkAZaOyYBd153A9hfY03aKR/zIV4UXDG7gjYyVd44mKxWgQQE9EEUpFckWTNjnH+wOWslXSrI8V5EKB8IGdUFWEt2aafdgVG9++P8cPNtd3XGfgsfmJuIJoskqhVCRbOn5Gg2maTKULdcJIM1jU4GTf73/PxGNP0PrSS5EV2fIircYk0Uycg5ODjCTHsSnWDWwikC+KfPfBCd75kwk++4dpxhPWupPIGewsuNhScLPP1zlvrCpbzOPQbIgItQTV+n6W4mumkMOp/X06qNociu/M6EuuVOE3Tw8f9TXNPrMmXAaAILL4E5+j5a2vQ37gHjbd8y0ADhSta/P08iA/bdzCpfZxTr7nW1QevI9TrrqAVeefTEXVsCka3rEhfIOWWFjR7iRTyCFguQfM7Mc2WcWju3Cq9mfFcipVZpl3+9ZczGjrSk6672Y2P9GHJIg1VVxTlMhWLX/ssal576PKCssaOlke6abVF6Fs1BfKWqqCpAIm/+K16Pdzyy6LbfOv37BU4HWewVrBEuBhe1ftGpoZhZiuKJim5X2sySpe3UXf9Aj9YwOkPvYVKrqLzRe/GQSBiMeOe9xiT6ZCTXOYgXkcqh3vEecu6PCyqW3F/6lxtIVwIkF9jrhsdX2Cmi2bvOQnP8Hb3s6uN78XZSpBupjFFARGl60FwDE9Scv2J/CMDuEZGcQzNkT3w3fT/sQDLHrgDoKH9jL47R9y6FNfxDj1bK5+uVU5+6F9HQfPeiGjy9cDlqLhkXjN6V2salxEV6AFQRAsKlhLA1tOfzlN/dtY/Ohv+WhuGU+v3kA6ZHVTDVnBmFO9ThWyNLqD7HQ18HDOy4+TTdw01cPv01bX1z/QaymWHqP6OxdHii3sGO1l10N/ZveXvor9orPpDyyrPRaJWRvjDGVpKm15bTZ5QvPUj4+Fdl8jp3euPSb17AT+ehAEgWZ3GKdmt4KZcpFsVXBIlmQUSbYSzwUCgJlYot3XSE+ojQ0ty+Y956+NZneIoMNLh7+Jdc1Lj+s12VLeoh3aHOyf7CeeS+HSHOiyik1WyRbz9E4NUSgXmUxPMxyfIJpNIGAScvhodP/trAyOB+HLrsIQRHq230WmIOCxOWtejACTXUsxZBktk6ZV0uifHmXn6EH2ThxmODFBeQ7d+Xjxm6cH+PaDg4wlk3VqhaokU6iUyc9J8J8c3E26kCVdyLK5bxtD8fGjvKuFH2zuq/t/2YBP31qi3UyyQrWKBblkmu6ffpZ1m39Kw6b1XPSfb0e1WcWJ8cWrKOv2mho1QG6OL2Ci0VqzkvkMIYePrkALAYeH6UwCTVYJO3xoVd/ro8Gu1q/pt2w7elA6A4dqw6nqGIZBrljg0YMLJw09EZVSpcxYcopMMUd3WKTROxsoJvMae8emyFRrADYFljcGOLtrPaubm1kUtu7VZY0qYaeXiDtIsyd8XKqSHt3JmqbFtPsb0WSNRneQdn8jyxo6a0HkM2FmLZmLZk8IWzVJLdg9bHjXe+i97XbyW3YRq3aiZmiKYqmI78Ae+ncc4P4f3cYP//0LPPiTPxDpbuO8732BZZ+6iegVLyFX1YwYS9TvbRevktg9dggTk55Np3LWr34IXj/n/P7TqPk0mYKAJAhMNbeRd3v5bLKHy4Y28qnpbsqITKWsZMOUZCqKagkmVSm+C+2jRwrhnFFNUB/I+THn9EMnUmUMRSXn8SMYJuboJE1ynm9GdtAm5+kr6bxpfAUVRSUTCFFwWsmFv78X99hg3WfkSzK7ho9+z4qCjiSKaLJKvlwkWzy+gpFpmrzqu0+w8WN38+5fbpv3eKdL5o5//VccPd10n7oaAchWf4diucRocooWb5hUIYNbnz32eNrD5gMi0xmDXcNFfve01WVOZCuUEHn7xHL62mb3D7PaIU4XczgUnTZfBLtqI1cqEMuliGYTDMTG8NvdNLlDf5cEQZMXZiMcnFhYxUcS4VVnOPi3F3TU/nbxigZetL6bsz54E02vfi3Ln76NU+/8CuPDE5imSblYpLD1Kdb+/BMsf+pWllx+HmsusgTx1FwWqZCnYf8OwPLpToat+Uq/7ibiCtQKqT2hdlZEumrn8XhRqsy5xgSRzS94K3KpwKr7foBhiFTmjI5lvdY4iSM2iXtsiMjuLejxWWaBIAiIgoBdtbFWnOamwAH0I9wpTrHFOat6/7xvagk/Tlpzve3SfLGpd/j6eKXbWnfvz/l54dBGdjpnZ6E7glasHDOsBFWujis0uAIEHR4SH/8Kpd5+dl/zDgrVkZ2lTgXvUB8wG9vmSgUwTZyaPs8v9gQsnKD4PkfYFIkPXLqMj91uqc5mimV0v5/rbrmFb59yCpOv/TdS//pq/BefS2egmbzLU+Ohl3Q7eZcH14Q1OK1MTTK6v5/93/gFhx7bTujSC7Fddi3OSj+P5L1kWusNloNH+MQtaXBxzuJF877jR65cyUfMa+kd2cfG+7+P2lRk/KyX0olF6RGYtS4ZT0Uplks4VBuhZg//cXB29miz2MT1jOMZHcQWDlOuHJ+P29gRFdORyUky7/0YhsvNrsvfgDFkffZiex5nJoEhy6QDVtCSyKdpdodY3tD1vImjnMDfBj2hVnRFJZqOM5qcQhIlwg5flc5q0RLDC/h9zswM21UbXYG/rYLiDDr8TTS4/M9I7Z2LJncQwzBI5jOWP1ypgKZYjIb+2Bguzc5YKsqByQF8uhtREBlLTtHua6Qz0HxM8Za/ByIdLTzccwo92+8iFnsnTR6Lqto3PUKjO4RLs5MKNOAZH6Ytm6McCjOZiSGLMn2xUQ5PjxBy+FjZ2H3Mz0kVsowlo0RTNt75CysoOn2xnXWtMt6hw3hGB4kHQgw7dHKlPCPxHPfs34PHXqjRWpO5NMVK+ajJjmma7BtP1f3NKZT5tHM34YlDPPG7XRx+ejeZ6QSyLHHKdS9k5dkbEKJWB3OubchcjKkKTYpKWdeJN7Vb/o1VX+JWbwPRTBynaseh2ZAkCa/qOiaNuz1Q/9jWgXjt35OpApoizrPpEgWRgMOLS3Mwlsxy5Ohqo1fi4pUOnLY8ByYncGsOBmNjlI0KGzu83Lq1StsuSAxNzwaOi8I2lke6qoVO+NFrT+ahg1Osa9cZTQ7QHWyl0V2/Jz0TZFGiK9BMqVKhJ9T6zC94BnT4G3HZdtdmIUuXvBz3t77Bwfd/HP8X349hGlaCappkf/UbfvaFb5GeTiDpNtqXddK5fhld65ex//QziB/x3qNzEtT/uMyPKI8RcUVwqDobWpbhtjl57INfxHz7y7jgV/9JYcOX0BoVpl1uMhvO4tZt43Xdmq0DBYZiUUIuFyWbjlQq4iyXq36o5Xksjd6p2YTkI+fJtB7Mk6pI7CzUs0kmktYPng40oMen0cZHOc8uYBcMRsoa755cykRFY/em81A1GffoEI17tgLQsH8nBYebQpUJMJ2enxyF3CaTSWuPzharHpeySiKfPm7rpz2jKR7Yb9Ef946l5j1u/vpmEv39tHzj04TzOUAg6wuSLeYZiI1WlU1dZEsFvDpMJK3f5rHe+sS+d8KKNWY8fAE8c2avR5KTpPNZJFHEabPT7AnTNz1CoVRkIj1NxOlnMhMn4PDQ7q9vPvytMFckaS6e6JuvY9DstfG1G7pQFWuOcU1LI7lihU2dfgRBoCfUiu3Tn+c/nuxj0c57Wbr1Dn7ociEUC5QLRexeF42XvoCzX7gRo+rdLFYqtGx/vKZKPrjuVAxMkrEMkVCgTnHapdlZ3djzrI/xReua+eyds77pSX8zuzdewcrHf0ti+xUoG3pmf3tdIwxWM2fEKqh4RwaoyDIlu5ORFRsoOpxs68vyDk8vAalEvKLw63SEeKZMj5LhRS6rePnLfCsPZX3oduue8RTTuGxBbrAdpl3J8aloFycxxv7Nu+nbupeB3lGuKpeQKyUe9nnRzzkZz2vfAKhWBxWQi7OMk8nPfYPkn+6n671v43eOjVC1qlkZ7UWsVEg2NJOrdoTHU1FCTkvB+x+JOfWPhBMJ6vMAhzZ3LsK68EPLlnHjI5v58TUvIX3Tf1O6/c9ob/t/eL1BGpJxMskMu4s2Jg/0Edj1NMm+IQZ3H6JcKCIpMste8gKW3Xgt3v5DmMCt6TAbnfWbR7FSoidS4cCY9fcPXlZv3zKDsxeHuPffzsd41zn8/g1vYPvNNzN4y+8Z1TRob8T9qqvpuuiiqu1Clg5fI4IgsrpVx6YkazLcfUUbeZcbWyrJ2due5Mn1pz5jB3U0kat5egFI5SKp938ODg9w19UfZnjIojZ4xBJv6kpBBlKhRkxJIl8qYBhGbc7pBP75oCs2dEWj0RUklkvi1V2sbuzh8PQwzZ5wTc30PRcvqW1Y/3bxkr/nVwYs/1RFenb0rk5/Mx6bi52j1nCPIAi0eMLYVRs2RcOuaLRIMolcGoeq49R00kVLvbdhgUT9742gU2PPhsvo2L+Zyv1/oPvVHyFbzKFIMv3RaZ48nMA1YuPfPCb26AS+9kV4dBe7x3otb8XkFGbYpFRpX5Cab5gGQ/EJeqODZIsFvnr3bCHr8KE8fu4lVLLUxvVEDFtPD4cns7zyW/dRrphcsaHIpatU4rkUiXwK9zHmyydThXmjBteM3cu+H/yMR0cmQBTJdq/izNP9NK/oJtIeqQsach7r97G63xYlO1PMM5GNM7VkKd2hNhBFoulpPDYnAbsHURAJO/2EnT50VePktpXYZPWYwcjiBhcfuWIFH7plFwAjiTzpQpktAzFe9Z3H0WSJP7z9TBK5EkOxLBcsa8CmSPjtHjy6k8f7xgAryQ04K9x4TpEWb5CKUWQslUBXNJo8IaazCeK5FO0BN2AFvum8AMJsEfD07qa6pCnisXH1Bqv63x38y0cnOvxNz/yk44QoiASdNiZTVpD477cd4Laf/Yzvn38eE6//AIevOR+HrtH39Rvpf3In/uYwGz79fuyXXUpz7048I4O1zvdcTKcrDFTVjAUBEKYxMfHYnJzasbp2PTecdBK3XP5uzr7lMxQ/936Ur/8HY/ECTx0us1Af8pePF7l8wzhdNh1bKkH35ARD4dZ5+6hpmhyatBJUFYONiUPERya5Z+sYPcUJxluWEQ+2Y4oSsYzBSCKB6AsQAoLJSc6vJmVfibczUVXkjxYlIrpEormdRFMbLdsfxzk5Rsv2xzl88jm0bnsMZ8bgiyyudWivXO9gPFFhsqq1oacTtD35BPFQhAFNOu6Z8KGjWPQBOBPj9H7vi/hfcB7Skhace/diyDJZh5uB6CBNnjAdvkYi7gBBu5dW/wT7x61rdvtQ/ftOpSxxsWR+NkG1qwYgkS3mSeUzNS/tZeHOGpPHY3NaM66aozZ68vcqiM8VSZqLoVh9MeCkDh/vuHAxq5tni0SrW7zzXhcJuHjo0nfwxHmvpWPvQ6xI7mNpl5fApg2crGSQJBEBy4JHLJVwTY6hJ2KYosj4ktUgCEyn49gVm6Ua/jx0lZu9Ot9+5UZe94NZNedtp13Hop33kvjIp6nc9Caiy7ppcocYTE7S09qJf/Bw3XtI5TJSMo5npJ/bxS72PXqIFweshsnVrjGudo0x/XQ/N0ditdf8KmqtWwdLdhAsNuO1fjvXSaOYhskben/Ob75yG7lUBtxeDiw/h5Ji4+KTQ6QOHSR12z2k7rifDasvI3rShdAAci4LmQyHvvhNhn/wc5pvfDnNr7me637zFKdEYnwh1kk4OoIpCEx2LyORTzMYG0OTVYJOH+2+v08h5J8BJxLU5wH11gBzJPqXr+Bfnnqae/7rs2z55Gc5cP2bOajISLpOOTlbRRwC9JCf8Isvo/HU9awR0iiqAkOHmanNPJH3cHG1Y2qaJiPJSWLZJFdt8PHUYTtn9bRwRs+xq9miJHHFN79BYWkr/Y88gl1USG5+gui//ifx7u/huOx8Wm+4jmZvmJ5gG5v7tvH68/N86Q5roU7lK4y1dNFRrb7qiRipwtE3HoBv3D9reC6VCpz/m49h9m/j4Re8jeFuSxjpPPsUHw4cRMlYm2KyoZlSpcxQYsYjLvi8eR+ewN8WXt1FszdMLJci4PCwONSOR3eytrk+Cb3x9A6cmkyTV2dl8z+Gku2zhSLJNLj8SOJiBCyrGpfmoFgp4VR1RFFkqb+JwfgYpkmNGtnsafiHvL5DLo2x1lXEgu147vkFsvgx1jYvIZ3T+do9aTIFk7DkwnSDEpuGqi9owOFlPD2NgUm2lCeRT9fRQGdov9tHDjAQH2cqPY0giIzGZzuDN7qH8OaSlABFspL91nSab/SmakqMtzylsqJ5pOY9W6lUalYuR6KOHmeabHroh7D5F1RCfqYvfzV3dF7Iq84JsX78AQSg5HBRcDhxTY6R8/op23QM0+Tg1BB2RWM0OUW+XKTF28BgbIwSJulcikQuxeJQO20+a3yi0R0iVyoQeAZxpLl41Wkd/OSxgVrHd9dwgg/9fheGac2iveUnT7NnNIlhwtKIix+97mSCDi9+uxvDiNfeJ+BUafW6GYyPo8kq7d5Gq6Pv9FOqlBEQCNr8zCSohZKCacqARXv7Z7kPX3N6B+/51XYAkvkyvg2buPHBB/nF9S/n7q/8DADFprLx8rNZfN3lDG86GwSB4UWrGFc89DoaKY8VWdSgIAgC+VKBO3ZN15K0tkAZh6YQdEZo8TbUFVsCDpW+pWegFDKccceXGX/nf3LLqusZ8C1e0G5ox6DARatgStdxAZF4jKlUouYpPpyYwKXZSeZEUvkKGmU+O/5THvz3hxk/ZM2wnVp9r4LmYLx1Bbs3XsnB8RUkXAU6VQ09n6dbgbQh8UR+9jeMZw0iHnj0YIb9Y2UuXLaOUwuPYEvGWXz/HwGIGCYr1DQ7iy42dMi8aL2THzycxCGUOU2P88LRw2gY2OPT6EuWki8Vj3rPTaTyhJwWk2TnyPz5QQBMg4vu/yYIAq43v5KOsnVvZ71+4oU0uqzR5A6ysrG7VvBp9eWZuWaPhGEKbB1M1PxhddVkKDGKS3OQyKeIuAK0+SK0ehtqdPE2X2Pt+R7dEjlr8Rz/ONHzjaN1UOfidWd08oGjNCSOhCKJdAZVDk+56d90CVdedAmLmyKIpRLy/X+oPS8ZbkYuFnBNWqyRZEMTRYezZvdl2cg8f2MoR64vJc3OfS/6dy770+dJvOED+K+8GOd7/xVNVunvaKbgdKNmM2R9AVq3PlZ7XaD/IHviKte45s/r+zMxRqMZ9hyc4FDvKJ2ZJ2iyuehbejqPBf2cIUxz+eiDPLp5G4O7DpKOxgl1tlB6w7v5lmjpDFy1wUn3Ogf7Jvroftsb6Pv8/7Dyrt/AE7/l7g0rCPidHHjXZ8jEUzS94hq6/+NfcRw+xMtmlLbDuxFMS5G4ZHcwHR2mxdOArmj0BNv+T9vIPBNOnJnnAc45HdRMob4SqtvsvPDfP4jj4rPYfsft2PrHETI57N2dfLk3SNLbSN7u4T2Xh+hp1qwg74E/QskSldlbcHBPNoCkyBQqk0QzDsCkUCrS5mskYHfzmlOXP6OS7gwkUaLjmqtInr4SUZRolN5M7vd3M/j720h+8bv03fkQG779HexNi7GrNuyKpf5nAsWywA5Fwt3ejb//IEIqxnhqmlZvw1FnPf+ww6Ivu6eHOeu2zxEcPcjh69/FgZZzAJPrXKP8i3cABEtdrWh3kPIFOTw9hEtzEHb56fg7UW1O4LlDEsWabHrFMI5KY7WrMq86reNv+M3+ejhyJk8XNU5qW4EqyWiySpM7RNko49TsTGUCBOzeBd/n742QSwNBYNfGKznjji9x51e/zTlveA03/e4wmYIV0U1UNCYrKhGxiJpJUXS6aXQHaXQHGU9Nkynkauq1AFOZOLvGejGxbFh2j07gsflJFSaJZa0CXIuc41z77IzRHbkGXmifoDmVZjBaP1IQdgbwOVy12d5H+3cQcHhwqDrtvsZat/LATIJqmrzoiW/j2/x7ek5Zg/NF1/DF2FoAIo0uhhpPxhWdIBlpJefxIZbLGLK1vsdzKRyKjWZP2PIGtblqnZZEPsN4Kkp3oIWuQHNtPZREkZ5Q27M+96tbPLUE9aXffLTusV0jswqse8dS/ObpIV5/Vjc9wTZ0KQVYIyRtfg8eXSVdyNHoDrIk3F4ze0/m0yiSTKMzBFgd/+lMhdwcdaVV/yQJ6jUbW/nkH/fW1GHHkwUWnbSJqx64lz9/7+s4xkY5pbMBwe2kf/UmEARM0+TLf06zpd8BWOfzwpV2DLNCxJNkcErHkjiCM3pcdAYC9IRa593bAadVdDiw5mJavRodt3yV8x99FxNNSxnq2sBE8zKibcspitb+bJgwEfeyI1DGq9vw5nJomRT7JvrIlwrsnxxAFiV+95SJXMxx9Z2fZMvup/E0+FGvfhk/aHghYqVMw9AuIoO7aO19nBf87P0Yu9fjfM9rGPL5aRkZYWfRyRdjHRiiBNWf9FO3TaPKJsWydU880pvn4xes4tT0w5iVCiaWsNO59ig7iy5e0pTDMz6Mrrj5bHgvK9U0kgFUnQR6pqdJhC1v4iMT1Pf+ajs/f3KQ85d5edmpMk8PLOyZevm+3+PZ8xhtN72bjM9OJGp1u7LeAJPpOK2eMG2+SF0BL+Q6dqFn+2CWmdDWZ5cplDPosoZLsxN2+unwN9WpTgcd3uOao/5bwXaUGdS5mLnujhdfftlqfvFUHz0Rg5I5zlQmTtDhrTHiypqNjD+EUSowE20lIxYFP5nP4NPddAaa6ui9zxU+x/yixnjrSpp+fBfuW7/O3m/czJP3Pkzgvf/C9IVnojd31J7Xv/EMSqqN7s13A/ARp8U4mU4XqExNkZqKMTUwSv/WvaSnrWvPUDRaVTtaLsXqx37Ftl+5OWAWKWXziLJE87Ju1l92Do516xg88yJe2l9EwOT0xSLDiQkcqo2mpZ20fPt/eNsXHqXpwd/Dlj8wZFRoWdbJma96EfI1VxN84E7EQqHGoBAESxhtYvFKy96oVKDd52BV4yJCTh8ncHScSFCfB8wVtljIXF0SRTo6FpO4QmAsHaXJE0ISdMa/P1F7znSVq44gMLJyA76BQ3xstI0/j1uL1QUrBFRZYCIVxQS6Ay20eMN0+puPOzmdwYyKaq6Ux+trJPjql+G85lIqDz5B/ye+yA/POpsLP/tZvC9/ER7dgaaUazTfeC5PXncAAt5yhb2JCSRR5JT2VZSNCpqs1DaTbLHMRKpAaHgPF/36I0jA5Evfwhlr2/DlxzjbPs0GzQoOZmrNo8vWkSxmUUWZdl+EtU1LTlSY/pfgH23G8m+JuXOHcylS/8ievC5NxmdXOLjqfHp23MXmd7+dg2Wdvmj9prqz4KRBmabhwE5ybh85j49MMILH5qQvOsxAdf62yRNi7/gAv3l6hKBTxG2X+OY9OoaZ4+Rui57rEUv8d3gPqmDy55yfj00tQhZMLmqfwJ1JYRRLgIImVDBMgXTeht9WwV4xyJbyZEt5kgWrA1g2KiwKWkHWrhErSFn30I/xbf49Ky46jZMuP5d/m+qYPV49w+OpLI2tHQQcVnJmKAqGaVAslYhm4jS5gyiyTMDhpcHpJ+IKEMsmGU5Ys50Rd+B5obBevaGFXz71zJ7ZACNxi2YZcvrw6xFmEtQOv4eloTCyILIk3FEXDK1pWkLZKCMKs3vHcHyWQuiyyfPmYf+RsSjk5PGM1VWbSOZZFHbi9waIvOgyBuPjjChOirqdimbdezuGCmw5wqLtrp0zbCCNmeQU4IrVy1jfFlpwH/I7Zs/fwXWXcOaNV/CLz/6YJVv+yLqHfoKAiaGqFNafwp3LriEW7mQwqnLu8k6i4+N4czlIJxhPWXZ0E+lpJpNw7+ZpLv3Fh1An+zj5qvMJ/uub+faAl9wO6zse8oRJnnwuj8WLLNn6R0568lccuuEtDK5dzpAZxohFWRUfZ63HzbCng74lpzHcuZ7inJAvVzT5wU6B/UYXFxj9JAyZHiXL2fZpthTcnDt6AGEU3izouNRZptT44pU07N9JQyrJZKVEtpSv2bcdnsrwtp9uYUdVgfiePXFWdWTpn9aAOYmXabLmkZ8TfPBHOF54LtmLTiakOXBP7AZgxOVGpULA6SXkqF9vGj3Hppg+cmBOh9sp4bW5aPE14Le76Q60HNMS6R8BR6P4zsWzvTdXNjewsrmBifQ0Tw2ZDMTGCDq8jC9ZjSM6wXTbIsqmwcH4GPmWFtokW82aJ1lI0+IOE3Q8v8nU0cSgnp6q8NFPfZHz3vZOfv7Saxl7/6eRvnwzk6tW4AiFkH0elFCAuw/BScY4y8QY472DTPQOEh+b7dQLooi5aCmPrr+OiaalTIc7MSUZLZek9eDjrIhtI9Lmoty2jP8prOHiYI6smiG0tIsGj8LFqyQORYcZSVSQRYmecBtLwu3YVR13+zhPqP+PbaddR1ugzNdWJHBNjcPOJylVTEwTthVcrKlaQ011LcWQFeKZBE5Vr7kdnMCxcSLyfx7g0GZvtGxx4ZnMNl8jsVwSURQZjk+QL9QHpn3RFBtKlmF0yukkvvoUNm+ZVaXsaczS4GzCcFQwTGuOZ0m4/S/6vnbFhs/uokkJ0R1owaO72DN+iKWvfj3OG97I71/zGv70rnexaWoC3w1XYFOmmRHi1SQnw0aSJsBXrpAp5YjlUuwZP8xkOoYkSWiSwvqWpfRNZWnf9zBn3fZ5XF4Xl7z5pbhDHmCCi48Y7/ijfSmLz1iCgcn45CAtnhCd/ub/8zLbJ3ACfy8IgsAHLl3Ou365jfte9B+88BcfRHj3a+i89B0cXnYW5yzx8ed9MW7PhDnHEcMRncQRtYRQkpFmDFGi1NpOX2wEQRA4GB3iV09Mc9vWmUJFBTBZpyUZ61cAnX/39xKWiuwuOvlktJsiIkUTDhtOuoU0rUaGvOjgu5HtlBAZPdDComwfi4A7FnWTU1QkQUQURHy6my5/M5++cx+/eHKIrl33sXbzz/Ceczqnvfgc9hWdPFalQK5tk5lKx2hyB4lmEwQcHjLFHJqkMJKcIlvM4VTtBBxeWr0N2BUbi0Nt2GSN4fgEIwh4dOfzVnDY1OlnZbObncPJZ3xudI6v5FR69t8hl0bEHSSygJCR5V1pJVcumzxvPndlk+efSrgj7J7tKI2nrITdqenYFRvlSpmk312zSeqPjfK7pyWON/xZ1bxwcgoQcc/uT6OJHIZ9CXs2XM6eDZejFLKcWd7NmvEtJO+4lysee4jtp17LgP+1NLqaGa16S9qLRRL5FB7dSSKf5t4HMlz8k5twpae46E3X0XzyGg41tuKcqBcXunR1iO9vnmT3xisJvOg6Luv/PU///HacsR2kPWGircuJiElaDzxGz867ybiC7F37QvavuZh8tWO4daDAVgJ8nQBg8qumLYSlIp8I7mfGOdVrZKkA/x3r4LG8l/ef2UKody+OfA4zm6Y/NkrY6adiwJt+9NQ8ESRV9DGdni0GSKUCZ/zxi3TteQD94nNY9In34RZEerY9jlipkPEFGDSKNLqDtHkj867Dkzrm32NXrWvmN1vmK16fvshLo9uky99co93/o0OTj13IVSSBM59hnOtoCDl8eGwOBEx2jh7Eoeo0tnWjyTLD8TF8upsxScFw+VGNMgOxMUzDxPE3tNy5ffsoDx+c4va3nckbH3+Ch37yfZ66+WYyB3rJPLmVciIFhkEnMAU8CJQ1nVjLUtwvfzGNazr5wQ6FqcbFdTZRMyjobg6uuoALz78c3Z2iK9DM9ftyJHMGi1c5UCQYT00TzcStwqqvibJRYUmooyaaGHHb2TOaoai7OJiFXyoRXtyg4Joa4/G0nV+mImwpuLnePcJJYQM90kKxXGIyPU2Hv6nGZDmBY+NEgvo8YG4HdTSe56r/eZhopsg3btjA0ogl7mNRHZegSArFcpE7D8eA2c3t7p0GOwajtPgFLlhVJJlx1tQY/Q6TRSEvYZefVm8DxXKJiPsvp1o0eUJUTIOw018THzq9c23t8at//nNuff3refyTn6Zl+zaall5FXLa6Am5bgHgxg4mJlk3js7nIFHJEs3EOTQ9TrpSrwiB+7vnY5znvd/9NpnkRr3jL5eguR9332Fpwc082wO/TYd5zid/yEEzF0KvKpyc8TE/gBP6+uGp9Mx+6ZRdp/Nz+sk9y/q8/yjm3fIbIxEE+8s7vcPa+h3g87+WtU8v55EkFAgOW76J7zAoWu1SVYmMzB6cG8eluHjlYBETsQoUb3MOcZZ+mVbYSipgh4xPLpA2J77CMG8/z87V7EpjAw0knnd4Up9jiXOaYICBZFbNIvJcKltXCWjTiDR2UjQp90yOkC1l+8fR2vnH/MJH+7Zzxhy8SbVvBK685B1EQ6WvsgREBm2Jyck+SNl8EXbExmpzi4NQgpmlSKBeRqh1Im6KyMtKNU7PXBRgBh4dWbwM+u/t5owoKgsBnXrKGq7++ueaFeDREq8H/tsF4baQCLJGr40HEbSOVr7ewOH/ZP1cA1TAnUZxIWudDFES8dhcOVWfvWIKtfTIRX5r1bR4mEgVYUMaoHmGXNs/6Zy4cmkzIpTGZKlCqmDx2aFaQ5ZqzW3jNGafgUHXkTIV3XPwK1m7+GVOHnyJ31vcwHJYab8AAQRA5PHyIzM/uZ8VPf4VSKnDam15Bx9JGxtu7QRCI5+oFiV516nK+v/l+APYmDN71tvfxXumi2uMtfoNwj8IvNhdoOfQUK574LRse/CGrHvs120+9lt4V55B1zU10BO7P+rnGNYYgQMYfJB1qpNw3zHcGPdyesa6J32zJsMjnxzU1jiM6zqTTw7aRfRwYdSyo0DsxKVApVgAJ7/QgZ9z6XwTHDrLj/Ffx5q+8BdGo0P7kQyi5LBVVpa+tC5EKAbtnQfG4Vr8duyrV3Rdvv6CHzb1RxpKz50gWBW48bQWCmJ/Xhf1HxjN1UE/rDuKyzafHHg8EQahZmsmSTL5UoC82gtfmwjAMwl4fUxmBaCZBvlwgYPdUPbojf1MGVDxb4jdPDfHW83s444Ybkc7cwJ7xw1RMA6NS4bZ7MwwOlZDKRUxBIBFoxRQl3n+Fg6IxyeR0fYdZEmGO9Sq6IrKuzUnvVJRipcQpi2TGUlGKFZFUoUSmkMWu2Ghyh1gSbkeRlLpr0e+oX1u/ubnAt4RmOoIdHJ6cHUP5TqKV8Jk+uk2DQ9PDhJ1+mtyhE93T48SJBPV5wNwZ1GimWKtof/vBw3zumjW1xyRRxCYGefTAMHftmN8ZHE+IjCdgacRPXzQOWItQZxhafA2sjHQ/L3RXh6qzNNxx1MdFSeKKb30Lf3c3D37845x8+x00d25g22nX4rO9BNVVIq/sxVYqseLQAR4PhxgTZkRiAoxODnPXR77A9G9vZ2rFabz01Reg69bqcE82wMeii3CIZZKGdXwXr7ITcKU5ODVBqVyiJ9RGT7Dtn6qCfwIn8L8RgiDQHrCzayRJQXdzx8s+waZ7v82yR3/DPVeNE1lxPWO+NrZnXexoaKS1pZOWbY8hGhWUXBbfUB+t/jDecDtj0+O83XaQ1Z4UfnG+PZWHIulklodt7dywrMCINEBXg4PecZlHc15e5hpdUAgDrOCjcd8OQkOHKel2inYPhyoJHj0YIzy0m/N/8zGSviZOfcsrsEkZUuFGQotDvM49SVcwQMgZoskTpFAuYldtyKJEqy/CRGoaQYBGd5Cl4Y4F16TuYCu6YqPNF3lexxGWN7n59ZtO4w87RjlrcQivrnDFVx6umxMFiKaLPNIb5WXfqp9VfaZZvRlcvqaJ/7prf+3/F69o4NX/ZPPg4TnHOp6c7db5dBdum4P/uSfNWLyELEqsbHSTLljjNaJgzYUeDcdDt+wMOJhMWZ/5532Ttb+f1tXOomCV7u2GkVe+n8GHNnLanV/l1nPPp+31r6A5bEOcThC6+xH2/voOCvEk/u5FBC6/khWLdQoeH6PBBkajQ0S8FSz6MXQE7LQHHNgUkXzJYDJV4OGD9cnh4gj0hH2Y0hSDPScz2HMyHfkJXrvvF6h3fI+N93+PycbF9C8+lcHuk0gEWvl1OsJaW5KcZse7fD1lm85Wo4nb98Zr73v3rhxXbJLYaEI4leaRhOWt+ced1n4uYHKSLYFfKvES5xgte8c4dXSQ3Y9sJ7n/IKga6g2v54INa2nd9ihqNoOazVDUHfRtOovB1BQBm6dO5f1IvGxTGzc/ZKm63nh6B+0BB//vrC4+etvu2nPecHYXDW47M6rW/yx4JpGkq9Y/N+u1Dn8TqqzgVO0cnBogkUsRyyboCbXRHWilWC4zkYrR4PLTHWx93uLOhfDyk9v4yWMDCz52994J3np+D6IgsjjUTqFcYjqbQDSd7MlFMY6oXZyzVKPMFO3+CGcuifLgPgWnZvDGC8o8flDlgaqrjU0RuenyFTS5S8RzCQ5Fh6kYFQJ2L33TIwhYlj2aotLlb17Qusyjzy8QmCZ1ySmArpiYwiiHogJBu4fOQDPLI11/2cn6P4gTCerzALu28Cb2q6eGagnqaCLHN+4/xPeOMItfCD9+JMNMcgqwvs3NokDL33QWUxBFznzf+9jwhjdw0xs/iP+PP+XSH7+X/qmHWf3O/8f+znWs3P84/skxNmZT5EQJc+8hBrbvZ+KhrRjRKLFzXsy7XrIcUTDoLdt589gKsqZ1rpKGwhmLVdZ1VNDUCdIF1bLecPpp80VqMy0ncAIn8PdFR9BRE+YxJIVHL3wTK887i8mbP8ULNr+F3uVns2/tC9k30I5zcSPxDadiV2y0Vm0s2p7eTM7loS2ewqykSByO0jsdZ3osysODRaRkjHBmnGwiDYZVyBqpfvY5PYtxh9Yz2H0Sd9t9XOCMMVS28dFoNxNljbihEJSK/LJpC+UKyJk0SibN6vI4v31sF8oj93JJ71OkPWH2v/y9vNs1CoLAUOdihhITrGuN0BVopt3XiF21MZacIpnPIIoiKxq6GHN4KRuVOsGlI+HS7H/xuMUzYVmjm2WNsxZbFy5v4JZtI3XPiWYKfP5P+458aV1X8Vj4l3O6OTiR5pZtI1yyKsIXXroWWfrnmhefe6wD05nav8NOP241xFjcmqEsG/CN+2a7xUsjTkYTBWLZhf28n6l7DdARtPN41aOyOKdN0xGoZwwtbXTxh6VnMNG8jNdu/wF9X/o2fXOPYVEb6155BY2LOyxRBlmmf9ka+hPjlvpsj51SQaI/WuJDl69AEgV6wq7avOfcQH9xROJVpzeyLNzFx26dnctzdC3ihv/+I7fd/iDf/My3aTvwCBvv/z4b7/8+ZUkhFurgm81LCYfsLN/yBAWvk4yzCd9kgLi/BbMag3xuS5gfRUYITkdZ3tTCgVScxw4rgMlrnX1cMPEo/dv2sWN3L5unrK6yw+dm3WVns/i0ddjdTgRhGGXKuqcqisLQmk2kTYNcsUCHr+mYHrtvv6CHZK6E167wrossRfjXnN7B6YsCNLhs2BQJXf3HnjU9GrQjiiLr27w8XfVD9tkVLl313EQjFUmuWZsUyhGmMglMTNp8Edp8EeK5FIVyEY/u/KsmpwDvvHAxAYfKskY3SyIuXvO9J+iPWvfq9qE4k6kCIZdGyOljU9sKYrkkP310CsO0RPR6GlSWN1fIFEqs6YgRcvhwanZesrHM+ctURDFNd6iVMzrdrGlOsqo5zIXLrbU8VypQMsp4UtNUjAp2TUeWRDRJpc0XYVlD51G/92S6cNTH5uL153iQpSlCDi+t3ggrI93/8DPQ/0g4kaA+D7Afo8q68kN3cvbiEI8citZUBp8tXrx2JYG/k8qcPRBAeukb+VXb+ax67Nesvfc33H/nLUw1dPPoqm5WVGJkYklG9vVRzBUQRIGGRe0IV1/DDatCiJjcmgmzM9xFdrT+vdd0pAi5VEKuViRBRJUVmt0huoPzfelO4ARO4O+DziMCbYB1N9zAuf/+Wj58/Vtpv+93LNp1H+ZPBLaGA0gtEXDaedJmw2eaeIp5MrEk0yMTpCZnKZCmIII3QtIdJNq8nsTSEBlngLM22Yg47agTcTKPPs2aR37B2s0/44DuplfTqJTKrDUqVCSZos1FUXPwXd3Aq5pQLFJJpcgnkrTni2guB/qFF/L0huv4cs8QUgmija3szyWIuAJ0+BvrOqMRd5Cwy49pWoyXv9e6ezS87fxF3LZ9pK7rN5Uu1s2egtUZXBQ+viKfLIl88bq1fPzFK/9i6uDfG3NnUO/eM8G+sRRLIi40WaVYCgL9tcf7orOCP0siHkqVRF2COrer8/bzFz3jZ3cE598fLk2ed/5XNXv5w44xcq4A+1/3ST76NZ0HfvB1GOpnSVczckMD9+cCXCZMIksCQ0tWcaCQqlLIIyyPdHHBkvqu+OKG2QR1rsjV+y9ZyZldTYiCyKdfsor3/noHAC89yRIN23jGSbzlwSTbT70WR3KS5oFtuCcHCI7uZ/G2PyFSYcI0arzIFwFlSSEaWcRI+1qGujcy4FdpU4ss2b2dZMnO4t0xzu27h9yeXdyZzSMpMlLPUnauuZLTlvgRW9pZ67Y6zE/mPWRdXpavCFHU7eR0ByO5BLHoBG1eywbmWImR26bw2TnsNLDYHjMjVf/MOLJr/4azu9k6GOexQ1Hef+ny57V4FHEHWF7uRJWVWkHAorTKNLmPPnv9fCHo1GoFBoD733Mu1379ER7vm8Y04fIvP8S1J7XyhrO6+Nydh+c1eF57Rg/dDRmKlTJlo4zH5qQr0MKh6BBSUMI0w/SE2tAVjbVHhJW6orGueQmJXJqKaaBKMsOJSTRZodV77HnlcxaHuPWIQuFcODWBr97QRNjlYTihEnR4WdXY839aKPIvwYkE9XmALIloskihbMx7LF0oc/uO0QVedfxYFvn78tW9doWKYmPrGdeze8MVdO+6j+5d91F88GH2SAZOh43Q6hX09pzCWWubWGGbmQMx+VGyiW8lWvmXjVk2Fjw8edgKBF66ycWpHU24bU68VRqWV3f9/Q7yBE7gBBZET0N9oL004uL8ZWFsioT/7Tfx7WUvpvXQk5xhjxHOjDK05xDG8BiKUSJXyTNaLFHS3djCbexbeQn9gR5WrA9wQIwwlLRRqsx2JiMeWP8iH52BZrqDluLm7x/YxRc/9z0a+7YiGhUMSaEiKUiVElo+hZrPMJEtMpUqI+h2Mr4mzl5SprUzQsfaZUiKzFXCIeQS5FxeNvs8hBxe2nwRloY753VGRUGclRX/B8OisIsvvWwd9+2d5NdPH13l9y3n9SCJx38QgiD80yanAEsj7hrdFeDzf9rHN19p+Ww/djh61NctCjv54876/fnDl6/AZ1cwTMvC5pmwUAHnBSsj8xKNsxYH+fQd1r//tGeCg5MOTjntFfz00SlOkeMcGHPg8kmsDplIDifbFBOf5qDN18jqpp4Fk4UlkflFiJBL47Tupho99tqNraiySKZQ4drq8TTMSegz7hD6C17CVSe18b7f7kBXBN57mUqbx4kzVyE1OMgf79pD/2M7CA/tZs0jP2fd5p9yx2/c2Nyu/9/enUdHWd97HH9/J5PJZA9ZmSyEEMMSAgQIO6IsVrAIraLSumuP9lpc2t7rxbv1nnNv7/Xc22OxvdUe637Vej3WHnGrVtSjtUpBrAuLZZcUJICsgQBJfvePZ4RJyIpmZhI+r3NymPk9zzPzG/iSeb7P8/39fgTq99NwqJ4xzY4jKUGKRwyh4ewZPOKrodYyAGMFkHIEGkpz2LP5ML85GOLyoT5cEBobj9Cwdz8ZSakMyy8jPz2bspwvPxN2b3Wk1USb0yryOH94z0zw5DMfZTktS4aT/IEO7x72tIXjS05UJHx2oIGfLVvP8k17WL655dq3w0IZXDR6AIE2JpVqvc56RyKr9bpaCTN3VIiXV3/GK2t2trl93qhippWPAKAgPYfMYJqS09PQpQTVzGYDd+PNE36/c+7OVtstvP0C4DBwjXNuVVeO7SvaSk47kxpI4JHrxvPYu1tZsWUvocwgK7fubbHP2RW5MR+LWVl48qrkseR01tbMY23NPAASaGZM8AAfHk3nqEvgyV2Ob6btZFxwH88dKuCPDf24/et+yvNymFmRx8sf11OWk8klNSX4zBfzzyYiHZtTFWLp0O1s23uY22YNZk7VyZk1y3JTaExKYfOwaWz+4oBO1o8/Z2iA80cHuNBv5KZms+uAcf9bOyjI8HH1lEIq8vJbTEgxf9pwJo3+N378woe89NEuvlYV5PkPGjp4B/gg4RgZvkYadvv4l5wNVAUP0ZCcwptFheRm5FCeW8zw/uW98qRh7shC5o4s5K31u6g7eGqp2ajiTK6fErsTzFjITg2w5LJqvvvYKgBeWbOT6x5ewdyRIR56e0u7x50zOI83/7LrxMlvVVEGAb+Pvzt/aJffe1L5qZP5XTz21CqgylAG+elJJ/7NNu2uZ9PuesB4p8G7CH3F2FQ+zx/N9v27CKXnUpxVwPD+g9q9kzW+7NT3vuvSUSRG3GUzM745umV/zIxp4c8OXsnsjKEFjBvYj+RAI86Okp3irSfMaJg5D974pI5rHlpB4MhBSjauoHDrnwkcOUh2qJwp+c30ryhl88AxHB9XyrYDRu1bJ5PgjKCx+MJEMpNLWVOwj1sSEinJTsTMSEzw4/clkJfaj6EFA733PIONGXDyhsS5Q/J6bany6bpgRIgfv7C2xezkrZPT9CQ/P/9WdZvJaTQk+RO476oanHPM/fkfWqxNXRnK4OaZFSe+I7+YiFS6r9ME1cwSgF8A5wG1wAozW+qcWxOx2xygIvwzAbgXmNDFY/uEBJ/R1NFsC3jrd1WGMpgzIsT86kIamxzJgQRqwtOmNzc71tcdIiWQwKInVrF5dz03TiuPRvc71NYX8Bea8LGiIevEc4fxzKH+PHPIu+J304x0pg8uIZSRS1ZyOmM6vyAtInEk4PfxwDXj2txW2sbdo44smpnD5RO8ssnG5sYTE6HMHTGMY42N4eVPTpWfHuTuheP592/UgxmpiRv4v5Xb8PuM/7hoBLc//WGL/Xc3Bdjd5L3WLTsruXF8PZmhAKHMfIqz8qksGNTrxwKlB/0tEtQnvjOBSeU5Z+xFv9lVIcrzUtm4yxuD+tq6Ol5bV9fu/k/eMJGqokxunVXBVQ/8iQSfcdel1d1+36yUAFdOLOV/3/XKiKcPyWNC2amzz5oZF48t5t43Nrb5OgNzA1xUPYQjx4+RlpRMcWYB5bnF7U4UBN7FiBavkZPC2RV5Xer34tleEl5dksX0Id4MvRUF7VcxjSrOAryL1BurZrCxasaJbX9MPEpZqInJI4IUZqUzNS+V51ft4fN6bwzvpeOKmTIoj6bmZrKSd5MZTCM7JQMzI8kfwO9LID0p5YyN3UgVBen814KRrNtxkJumx/78L9qCiQncMrOCHy1d3e4+D183jrPyY19xZ2bcf3UNL370GecMzmNQbiq+blSuSMe6cgd1PLDBObcJwMyeBOYDkUnmfOBR55wD3jWzLDMLAQO7cGyfMH1IHq+urcPvM356WTVPLP+UtKCf2r1HWLvjAOcOyWPJZdVkpZw8AWs9dNXnM4b09/7TPbtoKs3NLi6CPT89yFn5aWyoOzm5xNjSfrwXvts7fUgOdQePsnr7ye01A9P45wtLKc/NJy2pd82iJyJdU9bG+Lv2LBhbxA9njWrzJNRnvnaT00jpQe/9/mnuMIaF0hlelMm4gdnc8/qGFmMLIx3Dx/jqSgJ+H0UZeRRl5veJE+GzK/JOJGN3L6xm8lmntzZiXzK/uqjFjMSRfnrZKJ77YAcfbNvHf18ykomDvAuvk8tzeXvxDIL+BDJTTq/M+W+/NoTt+47Q2Oy48+KR7cbXD84bTHG/ZP7xtx+fsu37syoZEJ685ovy9s6YGYvnDOXOl9YBcMcFw7rc58rCDB69bnyX9++XGiA3LYndERPEZCYncs3kAcwcHuDg0YOkBILkpfajID2bZT9oPjG8acHY4hMlz4NyvtwstGeCS7tQWt6XfXvCAD6o3cczq1qubVtVlMFzi6bG1e/vUGYy1089sypWosW8nLKDHcwWALOdc98JP78SmOCcWxSxz/PAnc65P4SfLwP+Hi9B7fDYiNe4AbgBYMCAAWO3bt3aepe4tufQUZ5aWcuEQdktSjSamx37jhwnO7Xzk6949vDbm/nX59aQ5Pdx26zBXDFxAPe8sZHCzCCXTyhlT/0xvv2rd1lfd4gkv4/nb57a4dVYEen9nHMs+OU7Jy5WgXdn77c3TcY57y7Wm+t3MbR/BovnDG1RevhV+snLn/A/r284pd0MfnVlDbMqT10qoLc7dLSRx9/dyqC8NM7rg5/vdBxtbOLeNzay5NX1gFfZtGBMMfOqC5kSTuCdczE/wV2+aQ/L1tUxu6o/z77/V0qyU7h+6qnjobuisamZp9+rJTM5kTlfcobXzix59S8seXU9aUl+nrpxEsNC6TH/u5S+a+WWz7n24RUcbGgklBnkqRsnUZKtGx59iZm955yraXNbFxLUS4DzWyWZ451zN0fs8wLwn60S1NuBQZ0d25aamhq3cuXKrn4+iZKte+rJSgm0uQYUeCdML364g8rCDKqKMtvcR0T6lobjTazevp/hhZnsPXyM5MSEFpUi0XC8qZnfffwZA7JTKMlOITM5kd+v2UleehJjS7Uo+pmm7kADr6zZycRB2XFRCthXHG9qZsWWzxmQnUJxPyUK0vMOH2tky+7DlGQn9+qJ3KRtHSWoXSnxrQUi6w2KOblMXWf7BLpwrPQSnY03S0vyc+m4M7s0ReRME0xMYGypN+YulBmbCU4SE3xcOKrlzJ+zq3pm5kuJf/kZQa6Y2DNr057JEhN8TC5XKblET0rA32KiTjlzdKXeagVQYWZlZhYAFgJLW+2zFLjKPBOB/c65HV08VkRERERERKTzO6jOuUYzWwS8jLdUzIPOudVm9t3w9l8CL+ItMbMBb5mZazs6tkc+iYiIiIiIiPRqnY5BjQWNQRUREREREembOhqD2vtWKRcREREREZE+SQmqiIiIiIiIxAUlqCIiIiIiIhIXlKCKiIiIiIhIXFCCKiIiIiIiInFBCaqIiIiIiIjEBSWoIiIiIiIiEheUoIqIiIiIiEhcUIIqIiIiIiIiccGcc7HuwynMbBewNdb96EAusDvWnRBBsSjxQXEo8UKxKPFCsSjxIJ7jsNQ5l9fWhrhMUOOdma10ztXEuh8iikWJB4pDiReKRYkXikWJB701DlXiKyIiIiIiInFBCaqIiIiIiIjEBSWop+e+WHdAJEyxKPFAcSjxQrEo8UKxKPGgV8ahxqCKiIiIiIhIXNAdVBEREREREYkLSlC7ycxmm9knZrbBzBbHuj/Sd5lZiZm9bmZrzWy1md0abs82s9+b2frwn/0ijrkjHJufmNn5seu99DVmlmBm75vZ8+HnikOJOjPLMrOnzWxd+HfjJMWixIKZfT/83fyxmf3azIKKRYkGM3vQzOrM7OOItm7HnpmNNbOPwtt+ZmYW7c/SHiWo3WBmCcAvgDlAJfAtM6uMba+kD2sEfuicGwZMBL4XjrfFwDLnXAWwLPyc8LaFwHBgNnBPOGZFvgq3AmsjnisOJRbuBn7nnBsKjMKLScWiRJWZFQG3ADXOuSogAS/WFIsSDQ/jxVGk04m9e4EbgIrwT+vXjBklqN0zHtjgnNvknDsGPAnMj3GfpI9yzu1wzq0KPz6IdyJWhBdzj4R3ewT4RvjxfOBJ59xR59xmYANezIp8KWZWDHwduD+iWXEoUWVmGcA04AEA59wx59w+FIsSG34g2cz8QAqwHcWiRIFz7k3g81bN3Yo9MwsBGc65d5w3IdGjEcfEnBLU7ikCtkU8rw23ifQoMxsIjAaWAwXOuR3gJbFAfng3xaf0lCXA7UBzRJviUKJtELALeChcbn6/maWiWJQoc879FfgJ8CmwA9jvnHsFxaLETndjryj8uHV7XFCC2j1t1WZrGmTpUWaWBvwGuM05d6CjXdtoU3zKl2Jmc4E659x7XT2kjTbFoXwV/MAY4F7n3GignnAZWzsUi9IjwuP75gNlQCGQamZXdHRIG22KRYmG9mIvrmNSCWr31AIlEc+L8Uo6RHqEmSXiJaePO+eeCTfvDJdmEP6zLtyu+JSeMAWYZ2Zb8IY1zDCzx1AcSvTVArXOueXh50/jJayKRYm2WcBm59wu59xx4BlgMopFiZ3uxl5t+HHr9rigBLV7VgAVZlZmZgG8QcdLY9wn6aPCs6k9AKx1zt0VsWkpcHX48dXAsxHtC80syczK8Aa8/yla/ZW+yTl3h3Ou2Dk3EO933mvOuStQHEqUOec+A7aZ2ZBw00xgDYpFib5PgYlmlhL+rp6JN0+EYlFipVuxFy4DPmhmE8MxfFXEMTHnj3UHehPnXKOZLQJexpux7UHn3OoYd0v6rinAlcBHZvbncNs/AHcCT5nZ9XhfkpcAOOdWm9lTeCdsjcD3nHNNUe+1nCkUhxILNwOPhy8SbwKuxbvYrliUqHHOLTezp4FVeLH1PnAfkIZiUXqYmf0aOBfINbNa4Eec3nfy3+DNCJwMvBT+iQvmTdwkIiIiIiIiElsq8RUREREREZG4oARVRERERERE4oISVBEREREREYkLSlBFREREREQkLihBFRERERERkbigBFVERERERETighJUERERERERiQtKUEVERERERCQu/D8AJG8JDHrObAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,6))\n",
    "plt.plot( V[1+train_size:], label=\"Heston variance\", linewidth=3)\n",
    "plt.plot( V_kalm, label=\"Kalman variance\", color='darksalmon', linestyle='-', linewidth=2, alpha=10)\n",
    "plt.fill_between(x=range(len(h_test)) ,y1=V_up, y2=V_down, \n",
    "                 alpha=0.3, linewidth=2, color='seagreen', label=\"Kalman error: $\\pm$ 1 std dev \")\n",
    "plt.plot( smooth_h, label=\"RTS smoother\", color=\"maroon\" )\n",
    "plt.title(\"Out of sample tracking: using test data\"); plt.legend(); plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
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     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16,6))\n",
    "plt.plot(V[1+train_size:], label=\"Heston variance\", linewidth=3)\n",
    "plt.plot( V_kalm, label=\"Kalman variance\", color='limegreen', linestyle='-')\n",
    "plt.plot(var_test/dt, label=\"GARCH variance\", color='peru', linestyle='--')\n",
    "plt.plot( roll_var.values[train_size:], label=\"Rolling Variance\", linestyle='--', alpha=1, color=\"orchid\")\n",
    "plt.title(\"Out of sample tracking: comparison of different methods\"); plt.legend(); plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is not easy to compare the methods by looking at the plot. Let's have a look at the MSE (mean square error):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE Kalman:  0.000310967950616797\n",
      "MSE GARCH:  0.00036177545392460754\n",
      "MSE Rolling:  0.0003791184919051251\n",
      "MSE Smoother:  0.00021729917496004827\n"
     ]
    }
   ],
   "source": [
    "print(\"MSE Kalman: \", np.mean( (V[1+train_size:] - V_kalm)**2 ) )\n",
    "print(\"MSE GARCH: \", np.mean( (V[1+train_size:] - var_test/dt)**2 ) )\n",
    "print(\"MSE Rolling: \", np.mean( (V[1+train_size:] - roll_var.values[train_size:])**2 ) )\n",
    "print(\"MSE Smoother: \", np.mean( (V[1+train_size:] - smooth_h)**2 ) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The Kalman filter approach is the best!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## References\n",
    "\n",
    "[1] Giuseppe Cavaliere (2006) - \"Unit root tests under time-varying variances\"\n",
    "\n",
    "[2] Taylor, S. J. (1986) - \"Modelling Financial Time Series\"\n",
    "\n",
    "[3] Harvey, A. C., and Shephard, N. (1993) - \"Estimation and Testing of Stochastic Variance Models\"\n",
    "\n",
    "[4] Harvey, A. C., Ruiz, E., and Shephard, N. (1994) - \"Multivariate Stochastic Variance Models\"\n",
    "\n",
    "[5] Ruiz, E. (1994) - \"Quasi-Maximum Likelihood Estimation of Stochastic Volatility Models\""
   ]
  }
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